LabelEncoder: Label Encoder
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LabelEncoder R Documentation
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
$inverse_transform()encodes the data and keep a memory of encodings simultaneously
Arguments
- data
a vector or list containing the character / factor values
Public fields
input_datainternal use
encodingsinternal use
decodingsinternal use
fit_modelinternal use
Methods
Public methods
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-
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Method fit()
Usage
LabelEncoder$fit(data_col)
Arguments
data_cola 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$fit_transform(data_col)
Arguments
data_cola vector containing non-null values
Details
Fits and returns the encoding
Returns
encoding values for the given input data
Examples
data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
Method transform()
Usage
LabelEncoder$transform(data_col)
Arguments
data_cola 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$inverse_transform(coded_col)
Arguments
coded_cola vector containing label encoded values
Details
Gives back the original values from a encoded values
Returns
original values from the label encoded data
Examples
data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$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
deepWhether 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)
superml documentation built on May 29, 2024, 1:09 a.m.
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| LabelEncoder | R Documentation |
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
$transform()based on encodings learned in
fitmethod is applies the transformation$fit_transform()encodes the data and keep a memory of encodings simultaneously
$inverse_transform()encodes the data and keep a memory of encodings simultaneously
Arguments
- data
a vector or list containing the character / factor values
Public fields
input_datainternal use
encodingsinternal use
decodingsinternal use
fit_modelinternal use
Methods
Public methods
Method fit()
Usage
LabelEncoder$fit(data_col)
Arguments
data_cola 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$fit_transform(data_col)
Arguments
data_cola vector containing non-null values
Details
Fits and returns the encoding
Returns
encoding values for the given input data
Examples
data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$new()
lbl$fit(data_ex$Name)
data_ex$Name <- lbl$fit_transform(data_ex$Name)
Method transform()
Usage
LabelEncoder$transform(data_col)
Arguments
data_cola 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$inverse_transform(coded_col)
Arguments
coded_cola vector containing label encoded values
Details
Gives back the original values from a encoded values
Returns
original values from the label encoded data
Examples
data_ex <- data.frame(Score = c(10,20,30,4), Name=c('Ao','Bo','Bo','Co'))
lbl <- LabelEncoder$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
deepWhether 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)
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