KNeighborsClassifier {less}R Documentation

KNeighborsClassifier

Description

Wrapper R6 Class of caret::knnreg function that can be used for LESSRegressor and LESSClassifier

Value

R6 Class of KNeighborsClassifier

Super classes

less::BaseEstimator -> less::SklearnEstimator -> KNeighborsClassifier

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of R6 Class of KNeighborsClassifier

Usage
KNeighborsClassifier$new(k = 5)
Arguments
k

Number of neighbors considered (defaults to 5).

Examples
knc <- KNeighborsClassifier$new()
knc <- KNeighborsClassifier$new(k = 5)

Method fit()

Fit the k-nearest neighbors regressor from the training set (X, y).

Usage
KNeighborsClassifier$fit(X, y)
Arguments
X

2D matrix or dataframe that includes predictors

y

1D vector or (n,1) dimensional matrix/dataframe that includes labels

Returns

Fitted R6 Class of KNeighborsClassifier

Examples
data(iris)
split_list <- train_test_split(iris, test_size =  0.3)
X_train <- split_list[[1]]
X_test <- split_list[[2]]
y_train <- split_list[[3]]
y_test <- split_list[[4]]

knc <- KNeighborsClassifier$new()
knc$fit(X_train, y_train)

Method predict()

Predict regression value for X0.

Usage
KNeighborsClassifier$predict(X0)
Arguments
X0

2D matrix or dataframe that includes predictors

Returns

Factor of the predict classes.

Examples
knc <- KNeighborsClassifier$new()
knc$fit(X_train, y_train)
preds <- knc$predict(X_test)

knc <- KNeighborsClassifier$new()
preds <- knc$fit(X_train, y_train)$predict(X_test)

preds <- KNeighborsClassifier$new()$fit(X_train, y_train)$predict(X_test)
print(caret::confusionMatrix(data=factor(preds), reference = factor(y_test)))

Method get_estimator_type()

Auxiliary function returning the estimator type e.g 'regressor', 'classifier'

Usage
KNeighborsClassifier$get_estimator_type()
Examples
knc$get_estimator_type()

Method clone()

The objects of this class are cloneable with this method.

Usage
KNeighborsClassifier$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

caret::knn3()

Examples


## ------------------------------------------------
## Method `KNeighborsClassifier$new`
## ------------------------------------------------

knc <- KNeighborsClassifier$new()
knc <- KNeighborsClassifier$new(k = 5)

## ------------------------------------------------
## Method `KNeighborsClassifier$fit`
## ------------------------------------------------

data(iris)
split_list <- train_test_split(iris, test_size =  0.3)
X_train <- split_list[[1]]
X_test <- split_list[[2]]
y_train <- split_list[[3]]
y_test <- split_list[[4]]

knc <- KNeighborsClassifier$new()
knc$fit(X_train, y_train)

## ------------------------------------------------
## Method `KNeighborsClassifier$predict`
## ------------------------------------------------

knc <- KNeighborsClassifier$new()
knc$fit(X_train, y_train)
preds <- knc$predict(X_test)

knc <- KNeighborsClassifier$new()
preds <- knc$fit(X_train, y_train)$predict(X_test)

preds <- KNeighborsClassifier$new()$fit(X_train, y_train)$predict(X_test)
print(caret::confusionMatrix(data=factor(preds), reference = factor(y_test)))

## ------------------------------------------------
## Method `KNeighborsClassifier$get_estimator_type`
## ------------------------------------------------

knc$get_estimator_type()
[Package less version 0.1.0 Index]