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algorithm
Logistic Regression
beginner
supervised
parametric
classification
tabular
text
Logistic Regression turns a weighted sum of features into a probability for a class.
Mechanisms
weighted sum
probability link
Properties
interpretable
probabilistic output
Constraints
requires scaling
sensitive to outliers
Practical profile
Explainability
high
Training cost
low
Inference cost
low
Data appetite
low
Concepts to understand
Data Leakage
Loss and Optimization
Metrics
The Perceptron
Regularization