report.lm: Linear Regression Modeling HTML report
In Laurae2/Laurae: Advanced High Performance Data Science Toolbox for R

Description Usage Arguments Value Examples

This function creates a linear regression report as a HTML file. Cross-validation is mandatory. Add quiet = TRUE to the list of arguments to make the function "shut up" the massive verbose text.

report.lm(data, label, folds, normalize = TRUE, cleaning = TRUE,
  deficiency = TRUE, stats = TRUE, coefficients = TRUE,
  adv_stats = TRUE, plots = TRUE, output_file = "report.lm.html",
  output_dir = getwd(), open_file = TRUE, quiet = FALSE, ...)

`data`	Type: data.table. The data to fit a linear regression model on.
`label`	Type: vector. The label the data must fit to.
`folds`	Type: list of numeric vectors. The folds used.
`normalize`	Type: boolean. Whether features should be normalized before being fed to the linear model. Defaults to `TRUE`.
`cleaning`	Type: boolean. Whether NAs are set to 0 (if there are any). Defaults to `TRUE`.
`deficiency`	Type: boolean. Whether rank deficiency computation is done (kappa). Defaults to `TRUE`.
`stats`	Type: boolean. Whether machine learning statistics should be output for model performance diagnosis. When `TRUE`, also returns the metrics and the out of fold predictions. Defaults to `TRUE`.
`coefficients`	Type: boolean. Whether feature coefficients should be output. Defaults to `TRUE`.
`adv_stats`	Type: boolean. Whether advanced statistics should be done to analyze in depth the data. Defaults to `TRUE`.
`plots`	Type: boolean. Whether plotting of fitted values vs predicted values should be done. Defaults to `TRUE`.
`output_file`	Type: character. The output report file name. Defaults to `"report.lm.html"`.
`output_dir`	Type: character. The output report directory name. Defaults to `getwd()`.
`open_file`	Type: boolean. Whether to open the output report once it has finished computing. Defaults to `TRUE`.
`quiet`	Type: boolean. Whether to "shut up" while rendering the HTML file or not. Defaults to `FALSE`.
`...`	Other arguments to pass to `rmarkdown::render`.

Returns a list with the machine learning models (Models), the machine learning metrics ("Metrics"), the folds "Folds", the fitted values per fold ("Fitted"), the predicted values per fold ("Predicted") if they were computed. Otherwise, returns TRUE.

# No example.
## Not run: 
  library(Laurae)
  library(data.table)
  library(rmarkdown)
  library(RcppArmadillo)
  library(DT)
  library(formattable)
  library(matrixStats)
  library(lattice)
  library(R.utils)

## End(Not run)