rfVarSelect

<p>Float (0, 1): Fraction of variables in x to select. <code>p * ncol(x)</code>. May help to set to a fraction twice
what you expect to be the true fraction of useful variables, to reduce false negatives at the expense of false
positives which can be dealt by an appropriate learning algorithm.</p>

<p>Select important variables from a set of features based on RF-estimated variable importance</p>

Advanced Machine Learning and Visualization made efficient and accessible. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression, Survival Analysis), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and dynamic graphs.

Efstathios D. Gennatas

rfVarSelect: Variable Selection by Random Forest

Description

Usage

Arguments