run_models: This function run many models using the same data

In elpidiofilho/easyFit: Routines for fit classification and regression models in easy way

Description

This function run many models using the same data

Usage

run_models(df, models = ifelse(is.factor(df[, 1]), c("qda", "rf", "gbm",
  "C5.0"), c("lm", "cubist", "gbm", "rf")), formula = NULL,
  preprocess = NULL, index = NULL, resample_ = "cv", nfolds = 10,
  repeats = NA, tune_length = 5, cpu_cores = 0,
  metric = ifelse(is.factor(df[, 1]), "Kappa", "Rsquared"), seeds = NULL,
  verbose = TRUE)

Arguments

df	Training dataframe
models	chosen models to be used to train model. Uses algortims names from Caret package.
formula	A formula of the form y ~ x1 + x2 + ... If users don't inform formula, the first column will be used as Y values and the others columns with x1,x2....xn
preprocess	pre process
index	Users cross validation folds. Default = NULL
resample_	resample method 'boot', 'boot632', 'optimism_boot', 'boot_all', 'cv', 'repeatedcv', 'LOOCV', 'LGOCV','none', 'oob', 'timeslice', 'adaptive_cv', 'adaptive_boot', 'adaptive_LGOCV'
nfolds	Number of folds to be build in crossvalidation
repeats	number of repeats to resample method repeatedcv
tune_length	This argument is the number of levels for each tuning parameters that should be generated by train
cpu_cores	Number of CPU cores to be used in parallel processing
metric	metric used to evaluate model fit. For numeric outcome ("RMSE", "Rsquared)
seeds	generate random seeds to allow reproductible results
verbose	prints results during the execution of the function

Details

details

Author(s)

Elpidio Filho, [e-mail]

Examples

## Not run: 
models = c("ridge", "rf", "cubist",'pls','pcr','foba','gbm','glmboost')
fit_models = run_models(df,models = models)

## End(Not run)

elpidiofilho/easyFit documentation built on May 28, 2019, 8:36 p.m.