p.clean: Clean data by eliminating predictors with many missing values

In PLORN: Prediction with Less Overfitting and Robust to Noise

Clean data by eliminating predictors with many missing values

Description

Clean data by eliminating predictors with many missing values

Usage

p.clean(x, missing = 0.1, lowest = 10)

Arguments

x	A data matrix (raw: samples, col: predictors).
missing	A ratio of missing values in each column allowed to be remained in the data.
lowest	The lowest value recognized in the data.

Value

A data matrix (raw: samples, col: qualified predictors)

Author(s)

Takahiko Koizumi

Examples

data(Pinus)
train.raw <- Pinus$train
ncol(train.raw)

train <- p.clean(train.raw)
ncol(train)

PLORN documentation built on March 21, 2022, 9:11 a.m.