View source: R/general.indexes.R
general.indexes | R Documentation |
Calculates the confusion matrix, overall accuracy, overall error and the category accuracy for a classification problem and the Root Mean Square Error, Mean Absolute Error, Relative Error and Correlation for a regression problem.
general.indexes(newdata, prediction, mc = NULL)
newdata |
matrix or data frame of test data. |
prediction |
a prmdt prediction object. |
mc |
(optional) a matrix for calculating the indices. If mc is entered as parameter newdata and prediction are not necessary. |
A list with the appropiate error and precision measurement. The class of this list is indexes.prmdt
# Classification data("iris") n <- seq_len(nrow(iris)) .sample <- sample(n, length(n) * 0.75) data.train <- iris[.sample,] data.test <- iris[-.sample,] modelo.knn <- train.knn(Species~., data.train) prediccion <- predict(modelo.knn, data.test, type = "class") general.indexes(data.test, prediccion) # Regression len <- nrow(swiss) sampl <- sample(x = 1:len,size = len*0.20,replace = FALSE) ttesting <- swiss[sampl,] ttraining <- swiss[-sampl,] model.knn <- train.knn(Infant.Mortality~.,ttraining) prediccion <- predict(model.knn, ttesting) prediccion general.indexes(ttesting, prediccion)
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