Function reference • mlrmini

All functions

Dataset(): Create a Dataset object

Evaluator(): Build an Evaluator

EvaluatorAIC(): Evaluate performance through AIC

EvaluatorAUC(): Compute Area Under The Curve

EvaluatorAccuracy(): Compute Accuracy of a Classifier

EvaluatorBIC(): Evaluate performance through BIC

EvaluatorMAE(): Evaluate Predictions using the Mean Absolute Error

EvaluatorMSE(): Evaluate predictions using the Mean Squared Error

InducerLm(): Function to create an object of class InducerLm

InducerRpart(): Function to create an object of class InducerRpart

InducerXGBoost(): Function to create an object of class InducerXGBoost

Model(): Create a Model object

Split(): Create a Split object hosting available resampling strategies

SplitCV(): Create a SplitCV object

as.data.frame(<Dataset>): Create a data.frame object from a Dataset object

`configuration<-`(): S3 method configuration<- for class 'InducerLm'

configuration(<Inducer>): S3 method configuration for class inducer

configuration(): S3 method configuration

fit(<InducerLm>): Fit a Model using InducerLm

fit(<InducerRpart>): Fit a Model using InducerRpart

fit(<InducerXGBoost>): Fit XGBoost model using InducerXGBoost

fit(): S3 method fit

hp(): Hyperparameter This function return the name, type and range of hyperparameters

hyperparameters() hyperparameters(): S3 method hyperparameters

inducer2Env(): Add new inducer to environment

metainfo(<Dataset>): Print the meta Information of a dataset

metainfo(): S3 method metainfo

mlrmini mlrmini-package: mlrmini: mlrmini

modelInfo(<Model>): modelInfo: print out info of a model

modelInfo(): S3 method modelInfo

modelObject(<Model>): modelObject: get the print out of a model

modelObject(): S3 method modelObject

predict(<ModelLm>): Predict values for fit.InducerLm

predict(<ModelRpart>): Predict values for fit.InducerRpart

predict(<ModelXGBoost>): Predict values for fit.InducerXGBoost

predict(): S3 method predict

print(<Dataset>): A print method for Dataset objects

print(<Evaluator>): Print an Evaluator

print(<EvaluatorAIC>): Print an EvaluatorAIC

print(<EvaluatorAUC>): Print an EvaluatorAUC.

print(<EvaluatorAccuracy>): Print an EvaluatorAccuracy

print(<EvaluatorBIC>): Print an EvaluatorBIC

print(<EvaluatorMAE>): Print an EvaluatorMAE.

print(<EvaluatorMSE>): Print an EvaluatorMSE

print(<InducerLm>): S3 method print for class InducerLm

print(<InducerRpart>): S3 method print for class InducerRpart

print(<InducerXGBoost>): S3 method print for class 'InducerXGBoost'

print(<ModelRegression>): Printing Regression Models

print(<SplitInstanceCV>): Printing a SplitInstanceCV

resample(): Create a ResamplePrediction

set_cv_idx(): Set indices for k-fold CV with repetitions

`[`(<Dataset>): Subset a Dataset Object