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Logistic regression can handle categorical predictor variables, too. Similarly, the values to predict "red", "blue" were stored as strings. You can use numeric 0 and 1 if you wish. Logistic regression ...

A hierarchical logistic regression model is proposed for studying data with group structure and a binary response variable. The group structure is defined by the presence of micro observations ...

The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...