R tools Code

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Apirori Code:

 install.packages("arules")

> library(arules)

> data(Groceries)

> transactions <- Groceries

> summary(transactions)

> itemFrequencyPlot(transactions, support=0.1, cex.names=0.8)

> itemFrequencyPlot(transactions, support=0.05, cex.names=0.8)

> itemFrequencyPlot(transactions,topN=20)

> rules <- apriori(Groceries, parameter =

list(support = 0.009, confidence = 0.25, minlen = 2))

> inspect(head(sort(rules, by="lift"),5))

> install.packages("arulesViz")

> library("arulesViz")

> plot(rules, measure=c("support", "confidence"), shading="lift", interactive=FALSE)

> milk.rules <- sort(subset(rules, subset = rhs %in% "whole milk"), by = "confidence")

> summary(milk.rules)

> inspect(milk.rules)


=====================================


NaivesBayes Code :


install.packages("e1071") 

library(e1071) 

data("iris")

head(iris) 

tail(iris) 

print(iris) 

summary(iris)

index=sample(2,nrow(iris),prob=c(0.9,0.1),replace=TRUE) 

set.seed(1234)

train=iris[index==1,] 

train

summary(train) 

test=iris[index==2,] 

test

summary(test)

model=naiveBayes (Species~., data=train) 

pred=predict(model,test)

table(pred) 

table(test$Species,pred)





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