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#------------------ # Data Preparation #------------------ #Read datasets #Download the data from http://datascience.esy.es/wp-content/uploads/2018/03/CreditData-1.zip train <- read.csv("Credit_train.csv") test <- read.csv("Credit_test.csv") #Rows and Cols dim(train) dim(test) #Columns name colnames(train) colnames(test) #Show head(train) head(test) #------ # OneR #------ library(OneR) #remove all records with missing values train <- na.omit(train) test <- na.omit(test) #binning the numerical variable train.bin <- optbin(train) #train model.OneR <- OneR(DEFAULT~., data = train.bin, verbose = TRUE) summary(model.OneR) plot(model.OneR) #test pc <-NULL pc <- predict(model.OneR, test, type = "class") eval_model(pc,test) |
Ejemplo en R OneR
Mapa -> Predecir el Futuro (inferir) -> Modelizacion -> Clasificacion -> Un R -> Ejemplo en R
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