metafeatures: Extract meta-features from a dataset

In rivolli/mfe: Meta-Feature Extractor

Extract meta-features from a dataset

Description

This is a simple way to extract the meta-features from a dataset, where all meta-features from each group is extracted.

Usage

metafeatures(...)

## Default S3 method:
metafeatures(x, y, groups = "default", summary = c("mean", "sd"), ...)

## S3 method for class 'formula'
metafeatures(formula, data, groups = "default", summary = c("mean", "sd"), ...)

Arguments

...	Optional arguments to the summary methods.
x	A data.frame contained only the input attributes.
y	A factor response vector with one label for each row/component of x.
groups	A list of meta-features groups, "default" for traditional groups of meta-features or "all" to include all them. The details section describes the valid values for this parameter.
summary	A list of summarization functions or empty for all values. See post.processing method to more information. (Default: c("mean", "sd"))
formula	A formula to define the class column.
data	A data.frame dataset contained the input attributes and class The details section describes the valid values for this group.

Details

The following groups are allowed for this method:

"infotheo"

Include all information theoretical meta-features. See infotheo for more details.

"general"

Include all general (simple) meta-features. See general for more details.

"landmarking"

Include all landmarking meta-features. See landmarking for more details.

"model.based"

Include all model based meta-features. See model.based for more details.

"statistical"

Include all statistical meta-features. See statistical for more details.

"clustering"

Include all clustering meta-features. See clustering for more details.

"complexity"

Include all complexity meta-features. See complexity for more details.

"concept"

Include all concept variation meta-features. See concept for more details.

"itemset"

Include all itemset meta-features. See itemset for more details.

Value

A numeric vector named by the meta-features from the specified groups.

Examples

## Extract all meta-features
metafeatures(Species ~ ., iris)

## Extract some groups of meta-features
metafeatures(iris[1:4], iris[5], c("general", "statistical", "infotheo"))

## Use another summary methods
metafeatures(Species ~ ., iris, summary=c("min", "median", "max"))

rivolli/mfe documentation built on March 29, 2022, 11:08 p.m.