LinearRegression {less} | R Documentation |
LinearRegression
Description
Wrapper R6 Class of stats::lm function that can be used for LESSRegressor and LESSClassifier
Value
R6 Class of LinearRegression
Super classes
less::BaseEstimator
-> less::SklearnEstimator
-> LinearRegression
Methods
Public methods
Inherited methods
Method fit()
Fits a linear model (y ~ X)
Usage
LinearRegression$fit(X, y)
Arguments
X
2D matrix or dataframe that includes predictors
y
1D vector or (n,1) dimensional matrix/dataframe that includes response variables
Returns
Fitted R6 Class of LinearRegression
Examples
data(abalone) split_list <- train_test_split(abalone[1:100,], test_size = 0.3) X_train <- split_list[[1]] X_test <- split_list[[2]] y_train <- split_list[[3]] y_test <- split_list[[4]] lr <- LinearRegression$new() lr$fit(X_train, y_train)
Method predict()
Predict regression value for X.
Usage
LinearRegression$predict(X0)
Arguments
X0
2D matrix or dataframe that includes predictors
Returns
The predict values.
Examples
lr <- LinearRegression$new() lr$fit(X_train, y_train) preds <- lr$predict(X_test) lr <- LinearRegression$new() preds <- lr$fit(X_train, y_train)$predict(X_test) preds <- LinearRegression$new()$fit(X_train, y_train)$predict(X_test) print(head(matrix(c(y_test, preds), ncol = 2, dimnames = (list(NULL, c("True", "Prediction"))))))
Method get_estimator_type()
Auxiliary function returning the estimator type e.g 'regressor', 'classifier'
Usage
LinearRegression$get_estimator_type()
Examples
lr$get_estimator_type()
Method clone()
The objects of this class are cloneable with this method.
Usage
LinearRegression$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
Examples
## ------------------------------------------------
## Method `LinearRegression$fit`
## ------------------------------------------------
data(abalone)
split_list <- train_test_split(abalone[1:100,], test_size = 0.3)
X_train <- split_list[[1]]
X_test <- split_list[[2]]
y_train <- split_list[[3]]
y_test <- split_list[[4]]
lr <- LinearRegression$new()
lr$fit(X_train, y_train)
## ------------------------------------------------
## Method `LinearRegression$predict`
## ------------------------------------------------
lr <- LinearRegression$new()
lr$fit(X_train, y_train)
preds <- lr$predict(X_test)
lr <- LinearRegression$new()
preds <- lr$fit(X_train, y_train)$predict(X_test)
preds <- LinearRegression$new()$fit(X_train, y_train)$predict(X_test)
print(head(matrix(c(y_test, preds), ncol = 2, dimnames = (list(NULL, c("True", "Prediction"))))))
## ------------------------------------------------
## Method `LinearRegression$get_estimator_type`
## ------------------------------------------------
lr$get_estimator_type()
[Package less version 0.1.0 Index]