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to trigger action pipeline
PatelVishakh
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PatelVishakh
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No Assignment.
Error: "Invalid Notebook The Notebook Does Not Appear to Be Valid JSON"
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The files are there This is due to a issue in my editor so I didj via via web. I have done similar for past assignments |
PatelVishakh
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PatelVishakh
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Hi Pavan, I have forwarded this issue to Daniel Razavi who hopefully can help you render your assignment.
Unfortunately, I cannot review it without it rendering (like in python) because in lcr the the output needs to match and that is not checkable without executing it.
danielrazavi
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danielrazavi
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I reviewed your Jupyter notebook and found a syntax error on line 266, a missing comma at the end of the line. Adding that comma should fix the issue and allow the notebook to render correctly.
If you are unable to resolve it, you can instead download a fresh copy of the Assignment 1 notebook and copy your answers into it. This should also resolve the rendering problem.
Separately, I left comments throughout the notebook noting some issues in your code. Please review and address those as well.
Due to the number of tiny problems your submission has, I'm requesting for changes to be made.
| "outputs": [], | ||
| "source": [ | ||
| "# Your answer here" | ||
| "wine_dfshape[0]\n" |
| "outputs": [], | ||
| "source": [ | ||
| "# Your answer here" | ||
| "wine_dfshape[1]" |
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same issue as before, wine_dfshape is not defined so it doesn't understand what you're trying to access.
| "final_knn = KNeighborsClassifier(n_neighbors=best_k)\n", | ||
| "final_knn.fit(A_train, B_train)\n", | ||
| "B_pred = final_knn.predict(A_test)\n", | ||
| "accuracy = accuracy_score(A_test, B_pred)\n", |
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Are you sure this is how accuracy_score is supposed to be used?
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@danielrazavi and @PatelVishakh thanks for all the comments. I figured out the error it was since I was using pycharm and forgot to follow the instructions. I redid the whole thing in VS code and have this new PR ready |
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closing this PR as this is stale now @PatelVishakh @danielrazavi |
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UofT-DSI | LCR Assignment 1
What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)
panda data set, numpy usage, crossvalidation and model testing
What did you learn from the changes you have made?
panda, dataset, data inspection, Standardization and data-splitting, cross-validation, and Model testing
Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?
BA
Were there any challenges? If so, what issue(s) did you face? How did you overcome it?
new syntax, usage, logical
How were these changes tested?
local
A reference to a related issue in your repository (if applicable)
Checklist