This tutorial shows how to use Generalized Linear Modeling in H2O for model training and classification.

GLM is a regression algorithm which finds a best-fit hyper-plane through the training data; GLM models have coefficients for each feature. Logistic Regression is a variant of GLM where the magnitude of the coefficients is related to the features' predictive ability; large (absolute) magnitude means the feature predicts more strongly.

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