custom_full_glmnet: Custom GLMNET Function for simplicity

In canhakan/canhakan1: Helper Package for Spatio-temporal Time-Series Data

Description

Uses 'glmnet' package. Uses lambda.min from cv.glmnet for doing predictions on the test data. Returns the prediction results. For seeing Weighted Mean Absolute Error and Mean Absolute Error, set output to TRUE.

Usage

custom_full_glmnet(
  train,
  trainres,
  test,
  testres,
  perf = "mae",
  output = FALSE,
  seed = 42
)

Arguments

train	'x' for 'glmnet'
trainres	'y' for 'glmnet'
test	matrix of test data for returning predictions
testres	observations of the test data for printing WMAPE results
perf	type.measure for cv.glmnet. Default = 'mae'
output	set 'TRUE' for printing WMAPE results. Default = FALSE
seed	for setting seed. Default = 42

Value

The predictions of the glmnet model applied on the test data

canhakan/canhakan1 documentation built on Dec. 19, 2021, 1:48 p.m.