Notebook and helper files

Author: lucasmassemin

costs.py

@@ -0,0 +1,33 @@
+import numpy as np
+from hw_helpers import sigmoid
+
+
+def compute_mse(y, tx, w):
+    """
+    Compute the mean square error.
+    :param y: labels
+    :param tx: features
+    :param w: weights
+    :return: the mean square error
+    """
+    e = y - tx.dot(w)
+    mse = e.T.dot(e) / (2 * len(e))
+    return mse
+
+
+def calculate_loss(y, tx, w, lambda_=0):
+    """
+    Compute the negative log likelihood
+    :param y: labels
+    :param tx: features
+    :param w: weights
+    :param lambda_: regularization
+    :return: the negative log likelihood
+    """
+    # ***************************************************
+    # INSERT YOUR CODE HERE
+    # TODO
+    # ***************************************************
+    return (((-1)*(y*np.log(sigmoid(tx@w))+(1-y)*np.log(1-sigmoid(tx@w)))) + lambda_/2*w.T@w).mean()
+
+