load_model

load_model

Usage

load_model(name)

Arguments

name

the name of the model

Examples

load_model("sda")
#> $label
#> [1] "sda"
#> 
#> $library
#> [1] "sda"
#> 
#> $loop
#> NULL
#> 
#> $type
#> [1] "Classification"
#> 
#> $parameters
#>   parameter   class       label
#> 1  diagonal logical Diagonalize
#> 2    lambda numeric   shrinkage
#> 
#> $grid
#> function (x, y, len = NULL, search = "grid") 
#> {
#>     if (search == "grid") {
#>         out <- data.frame(diagonal = FALSE, lambda = seq(0, 1, 
#>             length = len))
#>     }
#>     else {
#>         out <- data.frame(lambda = runif(len, min = 0, 1), diagonal = sample(c(TRUE, 
#>             FALSE), size = len, replace = TRUE))
#>     }
#>     out
#> }
#> 
#> $fit
#> function (x, y, wts, param, lev, last, classProbs, ...) 
#> sda::sda(as.matrix(x), y, diagonal = param$diagonal, lambda = param$lambda, 
#>     ...)
#> 
#> $predict
#> function (modelFit, newdata, submodels = NULL) 
#> sda::predict.sda(modelFit, as.matrix(newdata))$class
#> 
#> $prob
#> function (modelFit, newdata, submodels = NULL) 
#> sda::predict.sda(modelFit, as.matrix(newdata))$posterior
#> 
#> $predictors
#> function (x, ...) 
#> {
#>     colnames(x$beta)
#> }
#> 
#> $levels
#> function (x) 
#> x$obsLevels
#> 
#> $tags
#> [1] "Discriminant Analysis" "Regularization"        "Linear Classifier"    
#> 
#> $sort
#> function (x) 
#> x[order(x$diagonal, x$lambda), ]
#>