29 lines
890 B
R
29 lines
890 B
R
library(kknn)
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library(caret)
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library(tidyverse)
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credit_data <- read.table("C:/Users/mjpearl/Downloads/data 2.2/credit_card_data.txt", stringsAsFactors = FALSE, header = FALSE)
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head(credit_data)
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#Utilize cross validation to
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# Split the data into training and test set
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set.seed(123)
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#Initialize the training dataset with a sample of an 80% partition using random split
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sample <- sample.int(n = nrow(credit_data), size = floor(.75*nrow(credit_data)), replace = F)
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train <- credit_data[sample, ]
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test <- credit_data[-sample, ]
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#Build the knn model using cross validation
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model <- lm(Fertility ~., data = train.data)
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# Make predictions and compute the R2, RMSE and MAE
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predictions <- model %>% predict(test.data)
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data.frame( R2 = R2(predictions, test.data$Fertility),
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RMSE = RMSE(predictions, test.data$Fertility),
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MAE = MAE(predictions, test.data$Fertility))
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