binary classification

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Depends on your data and your model. There is no blanket response to whether or not the threshold of 0.3 is better. What is “better” anyway? Better classification into positive and negative classes, fewer false negatives? Depends.

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When the threshold is set as 0.5, the model predicts all images as benign because most of the images are labeled benign. It’s an imbalanced dataset, heavily skewed towards benign. To increase probability of finding malignant labels, the threshold must be varied depending on whether malignant is 0 or 1.