The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

The predictive accuracy of 5 machine learning classifiers (logistic regression classifier, random forest classifier, support vector machine, k-nearest neighbor, and adaptive boosting) was examined ...

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

The C1 classifier assigned a relevance score (range: 0-1) to the test set corresponding to the likelihood that each abstract in R2 was relevant. The relevance score was calculated using an ensemble ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.

Purpose To build a decision tree for patients suspected of having prostate cancer using classification and regression tree (CART) analysis. Patients and Methods Data were uniformly collected on 1,433 ...

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...