Perceptron.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyNF8Ej/KH4WSV3dW5GxonQ/"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"cellView":"code","id":"kXzUG8OQgHr_","executionInfo":{"status":"ok","timestamp":1710827634917,"user_tz":-330,"elapsed":3614,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}}},"outputs":[],"source":["import numpy as np\n","import keras\n","import matplotlib.pyplot as plt\n","from keras.models import Sequential\n","from keras.layers import Dense\n","from keras.optimizers import Adam\n","%matplotlib inline"]},{"cell_type":"code","source":["n_pts = 500\n","np.random.seed(0)\n","Xa = np.array([np.random.normal(13, 2, n_pts),\n","               np.random.normal(12, 2, n_pts)]).T\n","Xb = np.array([np.random.normal(8, 2, n_pts),\n","               np.random.normal(6, 2, n_pts)]).T\n","\n","X = np.vstack((Xa, Xb))\n","y = np.matrix(np.append(np.zeros(n_pts), np.ones(n_pts))).T\n","\n","plt.scatter(X[:n_pts,0], X[:n_pts,1])\n","plt.scatter(X[n_pts:,0], X[n_pts:,1])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":447},"id":"cwrZ4UoGi290","executionInfo":{"status":"ok","timestamp":1710827635970,"user_tz":-330,"elapsed":1058,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"86735fb1-72a1-4c91-a6cb-cf4c196faf31"},"execution_count":2,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.collections.PathCollection at 0x7be5c3913d60>"]},"metadata":{},"execution_count":2},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["model = Sequential()\n","model.add(Dense(units=1, input_shape=(2,), activation='sigmoid'))\n","adam=Adam(lr = 0.1 )\n","model.compile(adam, loss='binary_crossentropy', metrics=['accuracy'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZOPogA96jjz1","executionInfo":{"status":"ok","timestamp":1710827636907,"user_tz":-330,"elapsed":956,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"c5386a72-d1aa-4d2d-e945-90be31432e26"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stderr","text":["WARNING:absl:`lr` is deprecated in Keras optimizer, please use `learning_rate` or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Adam.\n"]}]},{"cell_type":"code","source":["h=model.fit(x=X, y=y, verbose=1, batch_size=50,epochs=500, shuffle='true')\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jG3nhuVURWiL","executionInfo":{"status":"ok","timestamp":1710827670040,"user_tz":-330,"elapsed":33140,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"4bba60dd-c851-4c36-e193-9bbc9584f34b"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/500\n","20/20 [==============================] - 2s 4ms/step - loss: 2.1849 - accuracy: 0.4480\n","Epoch 2/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.1596 - accuracy: 0.4510\n","Epoch 3/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.1363 - accuracy: 0.4480\n","Epoch 4/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.1140 - accuracy: 0.4490\n","Epoch 5/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.0909 - accuracy: 0.4500\n","Epoch 6/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.0697 - accuracy: 0.4530\n","Epoch 7/500\n","20/20 [==============================] - 0s 4ms/step - loss: 2.0482 - accuracy: 0.4530\n","Epoch 8/500\n","20/20 [==============================] - 0s 2ms/step - loss: 2.0267 - accuracy: 0.4520\n","Epoch 9/500\n","20/20 [==============================] - 0s 2ms/step - loss: 2.0063 - accuracy: 0.4530\n","Epoch 10/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.9846 - accuracy: 0.4530\n","Epoch 11/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.9645 - accuracy: 0.4490\n","Epoch 12/500\n","20/20 [==============================] - 0s 3ms/step - loss: 1.9434 - accuracy: 0.4510\n","Epoch 13/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.9224 - accuracy: 0.4490\n","Epoch 14/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.9018 - accuracy: 0.4470\n","Epoch 15/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.8806 - accuracy: 0.4490\n","Epoch 16/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.8603 - accuracy: 0.4510\n","Epoch 17/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.8388 - accuracy: 0.4510\n","Epoch 18/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.8195 - accuracy: 0.4490\n","Epoch 19/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.7978 - accuracy: 0.4500\n","Epoch 20/500\n","20/20 [==============================] - 0s 3ms/step - loss: 1.7776 - accuracy: 0.4520\n","Epoch 21/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.7571 - accuracy: 0.4520\n","Epoch 22/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.7372 - accuracy: 0.4510\n","Epoch 23/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.7171 - accuracy: 0.4530\n","Epoch 24/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.6971 - accuracy: 0.4530\n","Epoch 25/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.6771 - accuracy: 0.4530\n","Epoch 26/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.6571 - accuracy: 0.4550\n","Epoch 27/500\n","20/20 [==============================] - 0s 3ms/step - loss: 1.6371 - accuracy: 0.4550\n","Epoch 28/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.6174 - accuracy: 0.4550\n","Epoch 29/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.5974 - accuracy: 0.4550\n","Epoch 30/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.5772 - accuracy: 0.4560\n","Epoch 31/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.5578 - accuracy: 0.4570\n","Epoch 32/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.5383 - accuracy: 0.4580\n","Epoch 33/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.5182 - accuracy: 0.4580\n","Epoch 34/500\n","20/20 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[==============================] - 0s 2ms/step - loss: 1.1674 - accuracy: 0.4820\n","Epoch 53/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.1509 - accuracy: 0.4830\n","Epoch 54/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.1335 - accuracy: 0.4850\n","Epoch 55/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.1172 - accuracy: 0.4870\n","Epoch 56/500\n","20/20 [==============================] - 0s 3ms/step - loss: 1.1005 - accuracy: 0.4870\n","Epoch 57/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0840 - accuracy: 0.4890\n","Epoch 58/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0680 - accuracy: 0.4900\n","Epoch 59/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0522 - accuracy: 0.4930\n","Epoch 60/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0365 - accuracy: 0.4980\n","Epoch 61/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0208 - accuracy: 0.5030\n","Epoch 62/500\n","20/20 [==============================] - 0s 2ms/step - loss: 1.0055 - accuracy: 0.4990\n","Epoch 63/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9906 - accuracy: 0.5040\n","Epoch 64/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9755 - accuracy: 0.5050\n","Epoch 65/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9605 - accuracy: 0.5100\n","Epoch 66/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9457 - accuracy: 0.5110\n","Epoch 67/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9313 - accuracy: 0.5160\n","Epoch 68/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9168 - accuracy: 0.5210\n","Epoch 69/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.9028 - accuracy: 0.5240\n","Epoch 70/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.8890 - accuracy: 0.5290\n","Epoch 71/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.8755 - accuracy: 0.5260\n","Epoch 72/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.8619 - accuracy: 0.5300\n","Epoch 73/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.8487 - accuracy: 0.5370\n","Epoch 74/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.8358 - accuracy: 0.5380\n","Epoch 75/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.8231 - accuracy: 0.5400\n","Epoch 76/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.8107 - accuracy: 0.5420\n","Epoch 77/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7982 - accuracy: 0.5470\n","Epoch 78/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7862 - accuracy: 0.5470\n","Epoch 79/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7743 - accuracy: 0.5500\n","Epoch 80/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7630 - accuracy: 0.5570\n","Epoch 81/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7516 - accuracy: 0.5640\n","Epoch 82/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7402 - accuracy: 0.5680\n","Epoch 83/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7291 - accuracy: 0.5760\n","Epoch 84/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.7185 - accuracy: 0.5800\n","Epoch 85/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.7087 - accuracy: 0.5880\n","Epoch 86/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6978 - accuracy: 0.5920\n","Epoch 87/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.6880 - accuracy: 0.6030\n","Epoch 88/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6782 - accuracy: 0.6070\n","Epoch 89/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6689 - accuracy: 0.6150\n","Epoch 90/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.6597 - accuracy: 0.6200\n","Epoch 91/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6506 - accuracy: 0.6330\n","Epoch 92/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6420 - accuracy: 0.6430\n","Epoch 93/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.6333 - accuracy: 0.6490\n","Epoch 94/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.6251 - accuracy: 0.6520\n","Epoch 95/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6173 - accuracy: 0.6540\n","Epoch 96/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6094 - accuracy: 0.6600\n","Epoch 97/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.6018 - accuracy: 0.6680\n","Epoch 98/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5945 - accuracy: 0.6740\n","Epoch 99/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5875 - accuracy: 0.6830\n","Epoch 100/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5804 - accuracy: 0.6910\n","Epoch 101/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5739 - accuracy: 0.6970\n","Epoch 102/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5673 - accuracy: 0.7060\n","Epoch 103/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5611 - accuracy: 0.7130\n","Epoch 104/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.5551 - accuracy: 0.7180\n","Epoch 105/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5492 - accuracy: 0.7300\n","Epoch 106/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5437 - accuracy: 0.7280\n","Epoch 107/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.5380 - accuracy: 0.7350\n","Epoch 108/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5327 - accuracy: 0.7470\n","Epoch 109/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5277 - accuracy: 0.7510\n","Epoch 110/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5225 - accuracy: 0.7550\n","Epoch 111/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.5178 - accuracy: 0.7650\n","Epoch 112/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5132 - accuracy: 0.7720\n","Epoch 113/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.5087 - accuracy: 0.7830\n","Epoch 114/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5044 - accuracy: 0.7940\n","Epoch 115/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.5003 - accuracy: 0.8140\n","Epoch 116/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4959 - accuracy: 0.8130\n","Epoch 117/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4923 - accuracy: 0.8200\n","Epoch 118/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4884 - accuracy: 0.8350\n","Epoch 119/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4847 - accuracy: 0.8430\n","Epoch 120/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4812 - accuracy: 0.8590\n","Epoch 121/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4775 - accuracy: 0.8580\n","Epoch 122/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4746 - accuracy: 0.8600\n","Epoch 123/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4710 - accuracy: 0.8710\n","Epoch 124/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4681 - accuracy: 0.8790\n","Epoch 125/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4649 - accuracy: 0.8760\n","Epoch 126/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4622 - accuracy: 0.8810\n","Epoch 127/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4593 - accuracy: 0.8700\n","Epoch 128/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4565 - accuracy: 0.8800\n","Epoch 129/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4537 - accuracy: 0.8890\n","Epoch 130/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4511 - accuracy: 0.8890\n","Epoch 131/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4486 - accuracy: 0.8920\n","Epoch 132/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4462 - accuracy: 0.8880\n","Epoch 133/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4439 - accuracy: 0.8890\n","Epoch 134/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4417 - accuracy: 0.9020\n","Epoch 135/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4393 - accuracy: 0.9020\n","Epoch 136/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4371 - accuracy: 0.9060\n","Epoch 137/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4350 - accuracy: 0.9030\n","Epoch 138/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4328 - accuracy: 0.9080\n","Epoch 139/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4308 - accuracy: 0.9080\n","Epoch 140/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4288 - accuracy: 0.9100\n","Epoch 141/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4270 - accuracy: 0.9100\n","Epoch 142/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4251 - accuracy: 0.9170\n","Epoch 143/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4234 - accuracy: 0.9210\n","Epoch 144/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4216 - accuracy: 0.9120\n","Epoch 145/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4197 - accuracy: 0.9170\n","Epoch 146/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4181 - accuracy: 0.9190\n","Epoch 147/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4164 - accuracy: 0.9200\n","Epoch 148/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4150 - accuracy: 0.9110\n","Epoch 149/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4137 - accuracy: 0.9090\n","Epoch 150/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4116 - accuracy: 0.9180\n","Epoch 151/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4101 - accuracy: 0.9250\n","Epoch 152/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4086 - accuracy: 0.9180\n","Epoch 153/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4072 - accuracy: 0.9230\n","Epoch 154/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4058 - accuracy: 0.9180\n","Epoch 155/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4042 - accuracy: 0.9230\n","Epoch 156/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.4029 - accuracy: 0.9200\n","Epoch 157/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4016 - accuracy: 0.9240\n","Epoch 158/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.4002 - accuracy: 0.9170\n","Epoch 159/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3988 - accuracy: 0.9200\n","Epoch 160/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3975 - accuracy: 0.9210\n","Epoch 161/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3962 - accuracy: 0.9210\n","Epoch 162/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3951 - accuracy: 0.9170\n","Epoch 163/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3938 - accuracy: 0.9230\n","Epoch 164/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3926 - accuracy: 0.9250\n","Epoch 165/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3912 - accuracy: 0.9210\n","Epoch 166/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3901 - accuracy: 0.9190\n","Epoch 167/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3889 - accuracy: 0.9160\n","Epoch 168/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3877 - accuracy: 0.9210\n","Epoch 169/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3866 - accuracy: 0.9180\n","Epoch 170/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3855 - accuracy: 0.9220\n","Epoch 171/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3843 - accuracy: 0.9190\n","Epoch 172/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3833 - accuracy: 0.9250\n","Epoch 173/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3820 - accuracy: 0.9230\n","Epoch 174/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3810 - accuracy: 0.9170\n","Epoch 175/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3801 - accuracy: 0.9220\n","Epoch 176/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3788 - accuracy: 0.9200\n","Epoch 177/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3777 - accuracy: 0.9200\n","Epoch 178/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3767 - accuracy: 0.9170\n","Epoch 179/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3756 - accuracy: 0.9210\n","Epoch 180/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3747 - accuracy: 0.9200\n","Epoch 181/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3738 - accuracy: 0.9210\n","Epoch 182/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3725 - accuracy: 0.9190\n","Epoch 183/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3716 - accuracy: 0.9220\n","Epoch 184/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3706 - accuracy: 0.9220\n","Epoch 185/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3696 - accuracy: 0.9180\n","Epoch 186/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3685 - accuracy: 0.9180\n","Epoch 187/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3676 - accuracy: 0.9250\n","Epoch 188/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3666 - accuracy: 0.9220\n","Epoch 189/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3656 - accuracy: 0.9220\n","Epoch 190/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3648 - accuracy: 0.9170\n","Epoch 191/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3637 - accuracy: 0.9200\n","Epoch 192/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3628 - accuracy: 0.9220\n","Epoch 193/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3618 - accuracy: 0.9240\n","Epoch 194/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3610 - accuracy: 0.9240\n","Epoch 195/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3599 - accuracy: 0.9250\n","Epoch 196/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3590 - accuracy: 0.9230\n","Epoch 197/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3582 - accuracy: 0.9180\n","Epoch 198/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3571 - accuracy: 0.9240\n","Epoch 199/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3562 - accuracy: 0.9240\n","Epoch 200/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3552 - accuracy: 0.9250\n","Epoch 201/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3544 - accuracy: 0.9250\n","Epoch 202/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3536 - accuracy: 0.9200\n","Epoch 203/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3528 - accuracy: 0.9250\n","Epoch 204/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3517 - accuracy: 0.9240\n","Epoch 205/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3508 - accuracy: 0.9250\n","Epoch 206/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3499 - accuracy: 0.9250\n","Epoch 207/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3490 - accuracy: 0.9250\n","Epoch 208/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3481 - accuracy: 0.9250\n","Epoch 209/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3473 - accuracy: 0.9240\n","Epoch 210/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3464 - accuracy: 0.9250\n","Epoch 211/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3455 - accuracy: 0.9250\n","Epoch 212/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3447 - accuracy: 0.9280\n","Epoch 213/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3437 - accuracy: 0.9240\n","Epoch 214/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.3430 - accuracy: 0.9240\n","Epoch 215/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3420 - accuracy: 0.9240\n","Epoch 216/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3412 - accuracy: 0.9240\n","Epoch 217/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3403 - accuracy: 0.9270\n","Epoch 218/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3396 - accuracy: 0.9240\n","Epoch 219/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3386 - accuracy: 0.9240\n","Epoch 220/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3378 - accuracy: 0.9290\n","Epoch 221/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3370 - accuracy: 0.9270\n","Epoch 222/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3362 - accuracy: 0.9270\n","Epoch 223/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3352 - accuracy: 0.9260\n","Epoch 224/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3344 - accuracy: 0.9290\n","Epoch 225/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3336 - accuracy: 0.9300\n","Epoch 226/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3328 - accuracy: 0.9290\n","Epoch 227/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3323 - accuracy: 0.9300\n","Epoch 228/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3311 - accuracy: 0.9290\n","Epoch 229/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3303 - accuracy: 0.9260\n","Epoch 230/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3295 - accuracy: 0.9260\n","Epoch 231/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3286 - accuracy: 0.9290\n","Epoch 232/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3281 - accuracy: 0.9340\n","Epoch 233/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3273 - accuracy: 0.9290\n","Epoch 234/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3263 - accuracy: 0.9280\n","Epoch 235/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3256 - accuracy: 0.9310\n","Epoch 236/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3247 - accuracy: 0.9340\n","Epoch 237/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3239 - accuracy: 0.9350\n","Epoch 238/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3231 - accuracy: 0.9330\n","Epoch 239/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3223 - accuracy: 0.9330\n","Epoch 240/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3215 - accuracy: 0.9300\n","Epoch 241/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3208 - accuracy: 0.9330\n","Epoch 242/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3202 - accuracy: 0.9380\n","Epoch 243/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3191 - accuracy: 0.9360\n","Epoch 244/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3183 - accuracy: 0.9330\n","Epoch 245/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3176 - accuracy: 0.9350\n","Epoch 246/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3169 - accuracy: 0.9370\n","Epoch 247/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3161 - accuracy: 0.9330\n","Epoch 248/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3153 - accuracy: 0.9360\n","Epoch 249/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3145 - accuracy: 0.9380\n","Epoch 250/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3138 - accuracy: 0.9370\n","Epoch 251/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3135 - accuracy: 0.9360\n","Epoch 252/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3123 - accuracy: 0.9380\n","Epoch 253/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3116 - accuracy: 0.9360\n","Epoch 254/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3106 - accuracy: 0.9390\n","Epoch 255/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3100 - accuracy: 0.9380\n","Epoch 256/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3092 - accuracy: 0.9390\n","Epoch 257/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3084 - accuracy: 0.9390\n","Epoch 258/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3076 - accuracy: 0.9370\n","Epoch 259/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3070 - accuracy: 0.9400\n","Epoch 260/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3066 - accuracy: 0.9390\n","Epoch 261/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3056 - accuracy: 0.9400\n","Epoch 262/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.3047 - accuracy: 0.9380\n","Epoch 263/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3040 - accuracy: 0.9390\n","Epoch 264/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3032 - accuracy: 0.9400\n","Epoch 265/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3030 - accuracy: 0.9390\n","Epoch 266/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3018 - accuracy: 0.9400\n","Epoch 267/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3011 - accuracy: 0.9380\n","Epoch 268/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.3005 - accuracy: 0.9400\n","Epoch 269/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2996 - accuracy: 0.9410\n","Epoch 270/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2988 - accuracy: 0.9410\n","Epoch 271/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2982 - accuracy: 0.9390\n","Epoch 272/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2974 - accuracy: 0.9400\n","Epoch 273/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2968 - accuracy: 0.9410\n","Epoch 274/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2961 - accuracy: 0.9380\n","Epoch 275/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2957 - accuracy: 0.9410\n","Epoch 276/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2945 - accuracy: 0.9400\n","Epoch 277/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2940 - accuracy: 0.9390\n","Epoch 278/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2931 - accuracy: 0.9400\n","Epoch 279/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2926 - accuracy: 0.9410\n","Epoch 280/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2918 - accuracy: 0.9410\n","Epoch 281/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2911 - accuracy: 0.9400\n","Epoch 282/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2904 - accuracy: 0.9410\n","Epoch 283/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2897 - accuracy: 0.9400\n","Epoch 284/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2891 - accuracy: 0.9420\n","Epoch 285/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2883 - accuracy: 0.9400\n","Epoch 286/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2878 - accuracy: 0.9400\n","Epoch 287/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2872 - accuracy: 0.9420\n","Epoch 288/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2864 - accuracy: 0.9420\n","Epoch 289/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2856 - accuracy: 0.9420\n","Epoch 290/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2850 - accuracy: 0.9450\n","Epoch 291/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2843 - accuracy: 0.9440\n","Epoch 292/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2836 - accuracy: 0.9430\n","Epoch 293/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2830 - accuracy: 0.9450\n","Epoch 294/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2822 - accuracy: 0.9440\n","Epoch 295/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2816 - accuracy: 0.9430\n","Epoch 296/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2809 - accuracy: 0.9430\n","Epoch 297/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2803 - accuracy: 0.9460\n","Epoch 298/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2797 - accuracy: 0.9460\n","Epoch 299/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2789 - accuracy: 0.9450\n","Epoch 300/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2783 - accuracy: 0.9450\n","Epoch 301/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2776 - accuracy: 0.9450\n","Epoch 302/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2770 - accuracy: 0.9460\n","Epoch 303/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2765 - accuracy: 0.9440\n","Epoch 304/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2758 - accuracy: 0.9460\n","Epoch 305/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2751 - accuracy: 0.9470\n","Epoch 306/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2745 - accuracy: 0.9460\n","Epoch 307/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2737 - accuracy: 0.9490\n","Epoch 308/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2732 - accuracy: 0.9460\n","Epoch 309/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2725 - accuracy: 0.9450\n","Epoch 310/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2719 - accuracy: 0.9460\n","Epoch 311/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2712 - accuracy: 0.9480\n","Epoch 312/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2707 - accuracy: 0.9490\n","Epoch 313/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2701 - accuracy: 0.9480\n","Epoch 314/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2693 - accuracy: 0.9480\n","Epoch 315/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2689 - accuracy: 0.9480\n","Epoch 316/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2682 - accuracy: 0.9520\n","Epoch 317/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2675 - accuracy: 0.9490\n","Epoch 318/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2670 - accuracy: 0.9520\n","Epoch 319/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2665 - accuracy: 0.9490\n","Epoch 320/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2657 - accuracy: 0.9510\n","Epoch 321/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2653 - accuracy: 0.9510\n","Epoch 322/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2645 - accuracy: 0.9500\n","Epoch 323/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2638 - accuracy: 0.9500\n","Epoch 324/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2633 - accuracy: 0.9490\n","Epoch 325/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2628 - accuracy: 0.9510\n","Epoch 326/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2622 - accuracy: 0.9500\n","Epoch 327/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2616 - accuracy: 0.9500\n","Epoch 328/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2610 - accuracy: 0.9520\n","Epoch 329/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2602 - accuracy: 0.9500\n","Epoch 330/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2597 - accuracy: 0.9500\n","Epoch 331/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2593 - accuracy: 0.9510\n","Epoch 332/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2585 - accuracy: 0.9510\n","Epoch 333/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2579 - accuracy: 0.9500\n","Epoch 334/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2577 - accuracy: 0.9520\n","Epoch 335/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2569 - accuracy: 0.9510\n","Epoch 336/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2562 - accuracy: 0.9500\n","Epoch 337/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2556 - accuracy: 0.9510\n","Epoch 338/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2551 - accuracy: 0.9530\n","Epoch 339/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2545 - accuracy: 0.9520\n","Epoch 340/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2539 - accuracy: 0.9540\n","Epoch 341/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2533 - accuracy: 0.9510\n","Epoch 342/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2528 - accuracy: 0.9520\n","Epoch 343/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2522 - accuracy: 0.9510\n","Epoch 344/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2517 - accuracy: 0.9520\n","Epoch 345/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2512 - accuracy: 0.9510\n","Epoch 346/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2507 - accuracy: 0.9550\n","Epoch 347/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2500 - accuracy: 0.9560\n","Epoch 348/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2498 - accuracy: 0.9530\n","Epoch 349/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2492 - accuracy: 0.9550\n","Epoch 350/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2485 - accuracy: 0.9540\n","Epoch 351/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2483 - accuracy: 0.9560\n","Epoch 352/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2476 - accuracy: 0.9540\n","Epoch 353/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2468 - accuracy: 0.9530\n","Epoch 354/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2464 - accuracy: 0.9540\n","Epoch 355/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2455 - accuracy: 0.9530\n","Epoch 356/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2451 - accuracy: 0.9520\n","Epoch 357/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2444 - accuracy: 0.9530\n","Epoch 358/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2442 - accuracy: 0.9570\n","Epoch 359/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2435 - accuracy: 0.9540\n","Epoch 360/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2429 - accuracy: 0.9530\n","Epoch 361/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2423 - accuracy: 0.9540\n","Epoch 362/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2420 - accuracy: 0.9530\n","Epoch 363/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2413 - accuracy: 0.9540\n","Epoch 364/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2407 - accuracy: 0.9550\n","Epoch 365/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2403 - accuracy: 0.9540\n","Epoch 366/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2398 - accuracy: 0.9550\n","Epoch 367/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2392 - accuracy: 0.9540\n","Epoch 368/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2387 - accuracy: 0.9540\n","Epoch 369/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2383 - accuracy: 0.9540\n","Epoch 370/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2378 - accuracy: 0.9550\n","Epoch 371/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2372 - accuracy: 0.9550\n","Epoch 372/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2369 - accuracy: 0.9540\n","Epoch 373/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2361 - accuracy: 0.9550\n","Epoch 374/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2358 - accuracy: 0.9550\n","Epoch 375/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2351 - accuracy: 0.9550\n","Epoch 376/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2346 - accuracy: 0.9550\n","Epoch 377/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2342 - accuracy: 0.9540\n","Epoch 378/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2336 - accuracy: 0.9540\n","Epoch 379/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2331 - accuracy: 0.9560\n","Epoch 380/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2327 - accuracy: 0.9550\n","Epoch 381/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2322 - accuracy: 0.9540\n","Epoch 382/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2316 - accuracy: 0.9550\n","Epoch 383/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2313 - accuracy: 0.9560\n","Epoch 384/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2306 - accuracy: 0.9560\n","Epoch 385/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2302 - accuracy: 0.9550\n","Epoch 386/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2297 - accuracy: 0.9560\n","Epoch 387/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2291 - accuracy: 0.9580\n","Epoch 388/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2287 - accuracy: 0.9580\n","Epoch 389/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2283 - accuracy: 0.9580\n","Epoch 390/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2277 - accuracy: 0.9570\n","Epoch 391/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2273 - accuracy: 0.9550\n","Epoch 392/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2268 - accuracy: 0.9570\n","Epoch 393/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2263 - accuracy: 0.9590\n","Epoch 394/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2258 - accuracy: 0.9590\n","Epoch 395/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2254 - accuracy: 0.9580\n","Epoch 396/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2250 - accuracy: 0.9600\n","Epoch 397/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2245 - accuracy: 0.9570\n","Epoch 398/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2240 - accuracy: 0.9590\n","Epoch 399/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2235 - accuracy: 0.9610\n","Epoch 400/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2230 - accuracy: 0.9590\n","Epoch 401/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2226 - accuracy: 0.9590\n","Epoch 402/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2224 - accuracy: 0.9610\n","Epoch 403/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2216 - accuracy: 0.9590\n","Epoch 404/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2213 - accuracy: 0.9590\n","Epoch 405/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2209 - accuracy: 0.9610\n","Epoch 406/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2203 - accuracy: 0.9590\n","Epoch 407/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2198 - accuracy: 0.9590\n","Epoch 408/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2193 - accuracy: 0.9600\n","Epoch 409/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2189 - accuracy: 0.9620\n","Epoch 410/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2185 - accuracy: 0.9620\n","Epoch 411/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2182 - accuracy: 0.9590\n","Epoch 412/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2176 - accuracy: 0.9600\n","Epoch 413/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2171 - accuracy: 0.9620\n","Epoch 414/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2167 - accuracy: 0.9620\n","Epoch 415/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2163 - accuracy: 0.9620\n","Epoch 416/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2158 - accuracy: 0.9600\n","Epoch 417/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2154 - accuracy: 0.9620\n","Epoch 418/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2150 - accuracy: 0.9620\n","Epoch 419/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2146 - accuracy: 0.9620\n","Epoch 420/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2140 - accuracy: 0.9610\n","Epoch 421/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2139 - accuracy: 0.9610\n","Epoch 422/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2131 - accuracy: 0.9600\n","Epoch 423/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2127 - accuracy: 0.9620\n","Epoch 424/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2123 - accuracy: 0.9620\n","Epoch 425/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2120 - accuracy: 0.9610\n","Epoch 426/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2116 - accuracy: 0.9620\n","Epoch 427/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2114 - accuracy: 0.9610\n","Epoch 428/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.2106 - accuracy: 0.9620\n","Epoch 429/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2102 - accuracy: 0.9620\n","Epoch 430/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2099 - accuracy: 0.9600\n","Epoch 431/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2094 - accuracy: 0.9620\n","Epoch 432/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2089 - accuracy: 0.9620\n","Epoch 433/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2084 - accuracy: 0.9620\n","Epoch 434/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2081 - accuracy: 0.9620\n","Epoch 435/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2078 - accuracy: 0.9610\n","Epoch 436/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2073 - accuracy: 0.9620\n","Epoch 437/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2069 - accuracy: 0.9620\n","Epoch 438/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2065 - accuracy: 0.9620\n","Epoch 439/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2061 - accuracy: 0.9620\n","Epoch 440/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2057 - accuracy: 0.9630\n","Epoch 441/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2055 - accuracy: 0.9620\n","Epoch 442/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2051 - accuracy: 0.9630\n","Epoch 443/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2048 - accuracy: 0.9620\n","Epoch 444/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2041 - accuracy: 0.9630\n","Epoch 445/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2037 - accuracy: 0.9630\n","Epoch 446/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2033 - accuracy: 0.9630\n","Epoch 447/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2029 - accuracy: 0.9620\n","Epoch 448/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2026 - accuracy: 0.9640\n","Epoch 449/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2023 - accuracy: 0.9630\n","Epoch 450/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2018 - accuracy: 0.9630\n","Epoch 451/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2013 - accuracy: 0.9630\n","Epoch 452/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2010 - accuracy: 0.9630\n","Epoch 453/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.2006 - accuracy: 0.9630\n","Epoch 454/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2002 - accuracy: 0.9630\n","Epoch 455/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.2000 - accuracy: 0.9630\n","Epoch 456/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1995 - accuracy: 0.9630\n","Epoch 457/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1991 - accuracy: 0.9630\n","Epoch 458/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1987 - accuracy: 0.9640\n","Epoch 459/500\n","20/20 [==============================] - 0s 4ms/step - loss: 0.1984 - accuracy: 0.9640\n","Epoch 460/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1980 - accuracy: 0.9630\n","Epoch 461/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1975 - accuracy: 0.9630\n","Epoch 462/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1972 - accuracy: 0.9630\n","Epoch 463/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1969 - accuracy: 0.9650\n","Epoch 464/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1965 - accuracy: 0.9640\n","Epoch 465/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1961 - accuracy: 0.9640\n","Epoch 466/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1958 - accuracy: 0.9630\n","Epoch 467/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1954 - accuracy: 0.9630\n","Epoch 468/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1951 - accuracy: 0.9640\n","Epoch 469/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1948 - accuracy: 0.9640\n","Epoch 470/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1943 - accuracy: 0.9640\n","Epoch 471/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1939 - accuracy: 0.9630\n","Epoch 472/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1935 - accuracy: 0.9640\n","Epoch 473/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1933 - accuracy: 0.9650\n","Epoch 474/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1928 - accuracy: 0.9650\n","Epoch 475/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1925 - accuracy: 0.9650\n","Epoch 476/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1921 - accuracy: 0.9650\n","Epoch 477/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1919 - accuracy: 0.9640\n","Epoch 478/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1914 - accuracy: 0.9640\n","Epoch 479/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1911 - accuracy: 0.9650\n","Epoch 480/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1907 - accuracy: 0.9650\n","Epoch 481/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1904 - accuracy: 0.9640\n","Epoch 482/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1900 - accuracy: 0.9650\n","Epoch 483/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1897 - accuracy: 0.9650\n","Epoch 484/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1894 - accuracy: 0.9650\n","Epoch 485/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1890 - accuracy: 0.9670\n","Epoch 486/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1887 - accuracy: 0.9660\n","Epoch 487/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1886 - accuracy: 0.9640\n","Epoch 488/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1878 - accuracy: 0.9640\n","Epoch 489/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1878 - accuracy: 0.9670\n","Epoch 490/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1873 - accuracy: 0.9680\n","Epoch 491/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1870 - accuracy: 0.9650\n","Epoch 492/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1869 - accuracy: 0.9670\n","Epoch 493/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1863 - accuracy: 0.9660\n","Epoch 494/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1860 - accuracy: 0.9650\n","Epoch 495/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1856 - accuracy: 0.9690\n","Epoch 496/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1853 - accuracy: 0.9670\n","Epoch 497/500\n","20/20 [==============================] - 0s 2ms/step - loss: 0.1850 - accuracy: 0.9670\n","Epoch 498/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1847 - accuracy: 0.9650\n","Epoch 499/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1843 - accuracy: 0.9670\n","Epoch 500/500\n","20/20 [==============================] - 0s 3ms/step - loss: 0.1842 - accuracy: 0.9680\n"]}]},{"cell_type":"code","source":["plt.plot(h.history['accuracy'])\n","plt.legend(['accuracy'])\n","plt.ylabel('accuracy')\n","plt.xlabel('epoch')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":466},"id":"mlxv8ooao7qK","executionInfo":{"status":"ok","timestamp":1710827670041,"user_tz":-330,"elapsed":38,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"43d9ad8d-57dd-4053-bcb6-c441f19444e1"},"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 0, 'epoch')"]},"metadata":{},"execution_count":5},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["plt.plot(h.history['loss'])\n","plt.legend(['loss'])\n","plt.title('loss')\n","plt.xlabel('epoch')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":489},"id":"0uYBAP_iRdut","executionInfo":{"status":"ok","timestamp":1710827670871,"user_tz":-330,"elapsed":853,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"6c8c9d77-294e-4a2d-a8e6-70d8a485a671"},"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 0, 'epoch')"]},"metadata":{},"execution_count":6},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 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\n"},"metadata":{}}]},{"cell_type":"code","source":["def plot_decision_boundary(X, y, model):\n","    x_span = np.linspace(min(X[:,0]) - 1, max(X[:,0]) + 1)\n","    y_span = np.linspace(min(X[:,1]) - 1, max(X[:,1]) + 1)\n","    xx, yy = np.meshgrid(x_span, y_span)\n","    xx_, yy_ = xx.ravel(), yy.ravel()\n","    grid = np.c_[xx_, yy_]\n","    pred_func = model.predict(grid)\n","    z = pred_func.reshape(xx.shape)\n","    plt.contourf(xx, yy, z)"],"metadata":{"id":"isbGVRIovk48","executionInfo":{"status":"ok","timestamp":1710827670872,"user_tz":-330,"elapsed":24,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["plot_decision_boundary(X, y, model)\n","plt.scatter(X[:n_pts,0], X[:n_pts,1])\n","plt.scatter(X[n_pts:,0], X[n_pts:,1])\n","\n","plot_decision_boundary(X, y, model)\n","plt.scatter(X[:n_pts,0], X[:n_pts,1])\n","plt.scatter(X[n_pts:,0], X[n_pts:,1])\n","x = 7.5\n","y = 5\n","\n","\n","point = np.array([[x, y]])\n","prediction = model.predict(point)\n","plt.plot([x], [y], marker='o', markersize=10, color=\"red\")\n","print(\"prediction is: \",prediction)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":499},"id":"B9_NYxVhvsKC","executionInfo":{"status":"ok","timestamp":1710827671950,"user_tz":-330,"elapsed":1101,"user":{"displayName":"Shivam Verma","userId":"14565644547298324714"}},"outputId":"f20bdd0c-7273-4190-e6ef-b0169b125dfd"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["79/79 [==============================] - 0s 1ms/step\n","79/79 [==============================] - 0s 2ms/step\n","1/1 [==============================] - 0s 40ms/step\n","prediction is:  [[0.9231803]]\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]}]}