Logistic Regression: Interpretation & Feature Engineering

In course

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Description

This lecture covers logistic regression, its probabilistic interpretation, and feature engineering techniques. Topics include overfitting/underfitting, train/test data, binary classification, logistic loss model, performance metrics, and data normalization methods.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_pqmm4kfx

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Cross-validation

Statistical inference: Mathematical statistics

Mathematics

Algebra: Linear algebra

Information engineering

Machine learning: Topics in machine learning

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