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Diabetes-classification-using-Bayesian-networks-in-R/BN_final.R
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| library(bnlearn) | |
| library(caret) | |
| df <- as.data.frame(lapply(df_over_under, factor)) | |
| trainIndex <- createDataPartition(df$Diabetes_binary, p = 0.8, list = FALSE) | |
| trainData <- df[trainIndex, ] | |
| testData <- df[-trainIndex, ] | |
| dag <- empty.graph(nodes = colnames(df)) | |
| dag | |
| dag <- set.arc(dag, from = "Diabetes_binary", to = "HighBP") | |
| dag <- set.arc(dag, from = "Diabetes_binary", to = "HighChol") | |
| dag <- set.arc(dag, from = "Diabetes_binary", to = "Stroke") | |
| dag <- set.arc(dag, from = "Diabetes_binary", to = "HeartDiseaseorAttack") | |
| dag <- set.arc(dag, from = "Age", to = "HighBP") | |
| dag <- set.arc(dag, from = "Age", to = "HighChol") | |
| dag <- set.arc(dag, from = "Age", to = "Diabetes_binary") | |
| dag <- set.arc(dag, from = "HighChol", to = "Stroke") | |
| dag <- set.arc(dag, from = "HighChol", to = "HeartDiseaseorAttack") | |
| dag <- set.arc(dag, from = "HighBP", to = "Stroke") | |
| dag <- set.arc(dag, from = "HighBP", to = "HeartDiseaseorAttack") | |
| dag <- set.arc(dag, from = "PhysActivity", to = "BMI") | |
| dag <- set.arc(dag, from = "BMI", to = "HighBP") | |
| dag <- set.arc(dag, from = "BMI", to = "HighChol") | |
| dag <- set.arc(dag, from = "BMI", to = "Diabetes_binary") | |
| dag <- set.arc(dag, from = "GenHlth", to = "Diabetes_binary") | |
| dag | |
| bn <- hc(df) | |
| dag2 <- empty.graph(nodes = colnames(df)) | |
| dag2 | |
| dag2 <- set.arc(dag2, from = "HighBP", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "HighChol", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "Stroke", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "HeartDiseaseorAttack", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "Age", to = "HighBP") | |
| dag2 <- set.arc(dag2, from = "Age", to = "HighChol") | |
| dag2 <- set.arc(dag2, from = "Age", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "HighChol", to = "Stroke") | |
| dag2 <- set.arc(dag2, from = "HighChol", to = "HeartDiseaseorAttack") | |
| dag2 <- set.arc(dag2, from = "HighBP", to = "Stroke") | |
| dag2 <- set.arc(dag2, from = "HighBP", to = "HeartDiseaseorAttack") | |
| dag2 <- set.arc(dag2, from = "PhysActivity", to = "BMI") | |
| dag2 <- set.arc(dag2, from = "BMI", to = "HighBP") | |
| dag2 <- set.arc(dag2, from = "BMI", to = "HighChol") | |
| dag2 <- set.arc(dag2, from = "BMI", to = "Diabetes_binary") | |
| dag2 <- set.arc(dag2, from = "GenHlth", to = "Diabetes_binary") | |
| dag2 | |
| plot(bn) | |
| plot(dag) | |
| plot(dag2) | |
| graphviz.plot(bn,shape = "rectangle", highlight = list(nodes = "Diabetes_binary", col = "blue", fill = "lightblue")) | |
| graphviz.plot(dag,shape = "rectangle", highlight = list(nodes = "Diabetes_binary", col = "blue", fill = "lightblue")) | |
| graphviz.plot(dag2,shape = "rectangle", highlight = list(nodes = "Diabetes_binary", col = "blue", fill = "lightblue")) | |
| fittedbn <- bn.fit(dag, data = trainData, method = "bayes") | |
| fittedbn | |
| fittedbn2 <- bn.fit(bn, data = trainData, method = "bayes") | |
| fittedbn2 | |
| fittedbn3 <- bn.fit(dag2, data = trainData, method = "bayes") | |
| fittedbn3 | |
| # Bayes-lw uses all available nodes and not just the parents | |
| pred = predict(fittedbn, node = "Diabetes_binary", data = testData, method = "bayes-lw") | |
| predhc = predict(fittedbn2, node = "Diabetes_binary", data = testData, method = "bayes-lw") | |
| pred2 = predict(fittedbn3, node = "Diabetes_binary", data = testData, method = "bayes-lw") | |
| # confusion_matrix | |
| confusion_matrix <- confusionMatrix(pred, mode = "everything", testData$Diabetes_binary) | |
| confusion_matrix | |
| confusion_matrixhc <- confusionMatrix(predhc, mode = "everything", testData$Diabetes_binary) | |
| confusion_matrixhc | |
| confusion_matrix2 <- confusionMatrix(pred2, mode = "everything", testData$Diabetes_binary) | |
| confusion_matrix2 |