Methods and apparatus to analyze uncertainty in machine learning models

An apparatus comprising:

• interface circuitry to obtain a multi-modal machine learning classifier;
• instructions;
• programmable circuitry to at least one of execute or instantiate the instructions to:
• determine uncertainty estimates for a plurality of modalities of the multi-modal machine learning classifier based on prediction distributions determined based on dropout analysis;
• determine modality importance scores for the plurality of modalities using two or more importance scores;
• determine modality-specific uncertainty scores for the plurality of modalities based on a combination of the uncertainty estimates and the modality importance scores;
• and
• trigger a corrective action based on the modality-specific uncertainty scores.

A system comprising:

• a classifier to perform classification using a multi-modal machine learning mode;
• and
• an uncertainty analyzer to:
• determine uncertainty estimates for a plurality of modalities of a multi-modal machine learning classifier based on prediction distributions determined based on dropout analysis;
• determine modality importance scores for the plurality of modalities using two or more importance scores;
• determine modality-specific uncertainty scores for the plurality of modalities based on a combination of the uncertainty estimates and the modality importance scores;
• and
• trigger a corrective action based on the modality-specific uncertainty scores.