SampleSizeTest: Test the affect of changing sample size on model performance

Description Usage Arguments Value

Description

Test how changing a model sample size affect model performance. Function requires separate training and test data. Currently only parallel processing using doParalell is supported, will add a non parallel version soon

Usage

1
SampleSizeTest(train, trainingY, testY, testX, sizes, NoCores)

Arguments

train

A dataframe/matrix containing a dependent variable and set of independent (predictor) variable used for model training

trainingY

Name of the dependent variable

testY

A vector of dependent variable to be used for model validation (testing)

testX

A data frame of predictor variables used for testing, row numbers MUST corespond to the values in testY

sizes

A vector of samples sizes to be tested

NoCores

Number of Cores to used to parallel processing

Value

A dataframe of model performance statistics for each sample size test. Metrics returned include coefficient of determination (Rsq), root mean squared error (RMSE), mean error (ME), mean absolute error (MAE).


Tomhigg/fracCover documentation built on May 9, 2019, 5:11 p.m.