LabelEncoder {superml}

Label Encoder

Description

Encodes and decodes categorical variables into integer values and vice versa. This is a commonly performed task in data preparation during model training, because all machine learning models require the data to be encoded into numerical format. It takes a vector of character or factor values and encodes them into numeric.

Format

R6Class object.

Usage

For usage details see Methods, Arguments and Examples sections.

lbl = LabelEncoder$new()
lbl$fit(x)
lbl$fit_transform(x)
lbl$transform(x)

Methods

$new()

Initialise the instance of the encoder

$fit()

creates a memory of encodings but doesn't return anything

$transform()

based on encodings learned in fit method is applies the transformation

$fit_transform()

encodes the data and keep a memory of encodings simultaneously

$inverse_transform()

encodes the data and keep a memory of encodings simultaneously

Arguments

data

a vector or list containing the character / factor values

Public fields

input_data

internal use

encodings

internal use

decodings

internal use

fit_model

internal use

Methods

Public methods

• LabelEncoder$fit()

• LabelEncoder$fit_transform()

• LabelEncoder$transform()

• LabelEncoder$inverse_transform()

• LabelEncoder$clone()

Method fit()

Usage

LabelEncoder$fit(data_col)

Arguments

data_col

a vector containing non-null values

Details

Fits the labelencoder model on given data

Returns

NULL, calculates the encoding and save in memory

Examples

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
decode_names <- lbl$inverse_transform(data_ex$Name)

Method fit_transform()

Usage

LabelEncoder$fit_transform(data_col)

Arguments

data_col

a vector containing non-null values

Details

Fits and returns the encoding

Returns

encoding values for the given input data

Examples

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)

Method transform()

Usage

LabelEncoder$transform(data_col)

Arguments

data_col

a vector containing non-null values

Details

Returns the encodings from the fitted model

Returns

encoding values for the given input data

Examples

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$transform(data_ex$Name)

Method inverse_transform()

Usage

LabelEncoder$inverse_transform(coded_col)

Arguments

coded_col

a vector containing label encoded values

Details

Gives back the original values from a encoded values

Returns

original values from the label encoded data

Examples

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
decode_names <- lbl$inverse_transform(data_ex$Name)

Method clone()

The objects of this class are cloneable with this method.

Usage

LabelEncoder$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
data_ex$Name <- lbl$fit_transform(data_ex$Name)
decode_names <- lbl$inverse_transform(data_ex$Name)

## ------------------------------------------------
## Method `LabelEncoder$fit`
## ------------------------------------------------

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
decode_names <- lbl$inverse_transform(data_ex$Name)

## ------------------------------------------------
## Method `LabelEncoder$fit_transform`
## ------------------------------------------------

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)

## ------------------------------------------------
## Method `LabelEncoder$transform`
## ------------------------------------------------

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$transform(data_ex$Name)

## ------------------------------------------------
## Method `LabelEncoder$inverse_transform`
## ------------------------------------------------

data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
decode_names <- lbl$inverse_transform(data_ex$Name)