Lecture

Quantifying Performance: Misclassification and F-Measure

In course

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Description

This lecture covers the estimation of data points from sampling, cross-validation techniques, quantifying performance through true positives, false negatives, and false positives, determining the optimal model, detecting overfitting, and the sensitivity of performance to various factors in machine learning.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_0llso0g0

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Ontological neighbourhood

Statistics

Data analysis: Cross-validation, Statistical classification

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