[EXTERNAL] Correct multi-class loss function to categorical_crossentropy#3028
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MSilva95 merged 1 commit into01-edu:masterfrom Oct 27, 2025
Merged
[EXTERNAL] Correct multi-class loss function to categorical_crossentropy#3028MSilva95 merged 1 commit into01-edu:masterfrom
MSilva95 merged 1 commit into01-edu:masterfrom
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correct multi-class loss function to categorical_crossentropy
HarryVasanth
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MSilva95
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Oct 27, 2025
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Why?
The README incorrectly stated that binary_crossentropy is the extension of log loss for multi-class classification. This is misleading because binary_crossentropy is only appropriate for binary or multi-label tasks, not single-label multi-class tasks.
Solution Overview
Updated the README to specify that categorical_crossentropy (or sparse_categorical_crossentropy if labels are integers) is the correct loss function for multi-class classification in Keras.
Implementation Details
Replaced reference to binary_crossentropy in the multi-class section with categorical_crossentropy.
Added a brief clarification on when to use sparse_categorical_crossentropy.
Left binary classification explanation unchanged.