predictlogisticRegression

test

<p>A vector containing the logistic regression parameters</p>

parameters

<p>This function returns a numeric vector containing the probability of each observation of being of class 1 given a vector of logistic
regression parameters (usually estimated through RCpp::fast_LR).</p>

A Stochastic-Expectation-Maximization (SEM) algorithm (Celeux et al. (1995) <https://hal.inria.fr/inria-00074164>) associated with a Gibbs sampler which purpose is to learn a constrained representation for logistic regression that is called quantization (Ehrhardt et al. (2019) <arXiv:1903.08920>). Continuous features are discretized and categorical features' values are grouped to produce a better logistic regression model. Pairwise interactions between quantized features are dynamically added to the model through a Metropolis-Hastings algorithm (Hastings, W. K. (1970) <doi:10.1093/biomet/57.1.97>).

Adrien Ehrhardt

glmdisc

Discretization and Grouping for Logistic Regression

Vincent Vandewalle

Christophe Biernacki

Philippe Heinrich

predictlogisticRegression function

Predicting using a logistic regression fitted with RCpp::fast_LR. — predictlogisticRegression

Predicting using a logistic regression fitted with RCpp::fast_LR.

predictlogisticRegression: Predicting using a logistic regression fitted with RCpp::fast_LR.

Description

Usage

Arguments