Removal of Classification Metrics #37
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updating Regression metrics In project which involves Stock Price Prediction which is a regression tasks, the objective is to predict continuous values, making these metrics irrelevant and potentially misleading when evaluating model performance. Since metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) are already implemented and are appropriate for this regression task, I suggest removing the classification metrics. This will help maintain clarity and focus on relevant performance indicators.
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Following Issue #35 is solved |
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@AnujSaha0111 please resolve the conflict |
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facing issues in resolving the conflicts |
jvedsaqib
requested changes
Oct 13, 2024
Mayureshd-18
requested changes
Nov 5, 2024
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@AnujSaha0111 Its been a long time since you have created this PR. Please update, resolve and make the requested changes as soon as possible.
Thanks and regards
Mayureshd-18
reviewed
Nov 9, 2024
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Closes #35
updating Regression metrics
In project which involves Stock Price Prediction which is a regression tasks, the objective is to predict continuous values, making these metrics irrelevant and potentially misleading when evaluating model performance.
Since metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) are already implemented and are appropriate for this regression task, I suggest removing the classification metrics. This will help maintain clarity and focus on relevant performance indicators.