Metrics for Classification

In course

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Description

This lecture covers the estimation of data points through sampling, the concept of cross-validation to confirm experimental findings, quantifying performance using metrics like True Positives and False Negatives, determining the optimal model, detecting overfitting, and the sensitivity of performance to various factors in classification.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_x9xzmoel

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Ontological neighbourhood

Statistics

Data analysis: Cross-validation

Data collection: Statistical sampling

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