Logistic Regression Assumption Checker

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Load Example Dataset

Choose a preset to auto-fill all fields

Dataset Properties

Number of features (predictors) Total sample size (n) Number of positive events (Y=1) Outcome type

Independence

Data collection method

Multicollinearity

Highest VIF among features

2.0

Highest pairwise |correlation|

0.30

Linearity in Log-Odds

Have you checked the Box-Tidwell test? Lowess / GAM smoothed plots

Outliers

Outlier situation

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Configure your dataset properties on the left,
then click Run Assumption Check to see results.

Part of ML-II: Supervised Learning Classification by Dr Milan Amrut Joshi