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rare (version 0.1.1)

Linear Model with Tree-Based Lasso Regularization for Rare Features

Description

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2018) . The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

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Install

install.packages('rare')

Monthly Downloads

186

Version

0.1.1

License

GPL-3

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Maintainer

Xiaohan Yan

Last Published

August 3rd, 2018

Functions in rare (0.1.1)

data.rating

TripAdvisor hotel review ratings
group.plot

Visualize groups by coloring branches and leaves of an hclust tree
group.recover

Recover aggregated groups of leaf indices
find.leaves

Find all descendant leaves of a node in an hclust tree
data.dtm

Document-term matrix for adjectives in TripAdvisor hotel reviews
tree.matrix

Generate matrix A encoding ancestor-descendant relationships in an hclust tree
data.hc

Hierarchical clustering tree for adjectives in TripAdvisor data set
rarefit.cv

Perform K-fold cross validation
rarefit.predict

Make predictions from a rarefit object and a rarefit.cv object
rare-package

Model path for tree-based lasso framework for selecting rare features
rarefit

Fit the rare feature selection model