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

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...

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 ...

Logistic regression analysis of high-dimensional data, such as natural language text, poses computational and statistical challenges. Maximum likelihood estimation often fails in these applications.

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 ...

During the making of an AI model, Performance metrics like accuracy, precision, recall, F1-score, ROC curves are used to ...

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