An R package for selecting variables in regression models

An implementation of the Panning Algorithm

Repositorio que contiene los scripts y explicaciones en R para elaborar un estudio del data set Titanic por medio de un proceso de preprocesado de datos, regresión logística para la selección de variables y árboles de decisión. Prácticas de la asignatura Tratamiento Inteligente de Datos.

One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Ga…

An R package that performs stepwise forward and backward feature selection

Feature engineering in machine learning

An R package to compute scores for different regression models.

Package corrplot is for visualizing a correlation matrix

An Efficient Gaussian Kernel Based Fuzzy-Rough Set Approach for Feature Selection

Compared the mean square error and R-Square value using linear model, Lasso and ridge regression

Auto Feature Selection in R

A new algorithm for feature selection

multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles

This web application is motivated by Baymax of the animated movie Big Hero 6. It detects Valvular Heart disorder i.e. damage or defect in one of the four heart valves. On the Machine Learning side, I have used AutoML from the deep learning platform H2O. And the interactive application is build in RShiny.

Titanic Project

Applied Least Square, Ridge and Lasso regression models to predict the number of comments a blog post will receive

R implementation of the Non-dominated Sorting Genetic Algorithm III for multi objective feature selection

The GFSM algorithm

Feature Selection using Elastic net function in the glmnet R package