資料探勘實驗（五） 樸素貝葉斯分類方法 R語言

了解樸素貝葉斯演算法基本原理；

能夠使用樸素貝葉斯演算法對資料進行分類

編寫函式實現示例資料集輸出結果。

rstudio

準備資料data，希望分類的元組x為test

主函式 *****bayes = function(){}

公式 p(ci|x) = p(x|ci) p(ci) / p(x)

求p(c1),p(c2)

pxi_ci = function(data,test,class_result){}

得pxi_c1，pxi_c2

p(x|c1) = p(x1|c1)*p(x2|c1)*p(x3|c1)…

p(x|c2) = p(x1|c2)*p(x2|c2)*p(x3|c2)…

測試*****bayes(data,test)

data

age=c(
"youth","youth","middle_aged","senior","senior","senior","middle_aged","youth","youth","senior","youth","middle_aged","middle_aged","senior"
), income=c(
"high","high","high","medium","low","low","low","medium","low","medium","medium","medium","high","medium"
), student=c(
"no","no","no","no","yes","yes","yes","no","yes","yes","yes","no","yes","no"
), credit_rating=c(
"fair","excellent","fair","fair","fair","excellent","excellent","fair","fair","fair","excellent","excellent","fair","excellent"
), buys_computer=c(
"no","no","yes","yes","yes","no","yes","no","yes","yes","yes","yes","yes","no))
#yes
test
yes",credit_rating="fair")
*****bayes = function(data,test)
pc = c() 
for (i in 1:length(class_result)) 
pc[1] 
pc[2]
#####求p(xi|ci)
pxi_ci = function(data,test,class_result)
}} temp = subset(data,data[,ncol(data)] == class_result)
pxi_ci = xcount/nrow(temp)
return(pxi_ci)
} pxi_c1= pxi_ci(data,test,class_result[1]) #"no"
pxi_c2= pxi_ci(data,test,class_result[2]) #"
yes"
#####求p(x|ci) 
px_ci = function(pxi_ci)
return(result)
}px_c1 = px_ci(pxi_c1)
px_c2 = px_ci(pxi_c2)
#######p(ci|x)
ci_x = data.frame(c1_x = px_c1*pc[1],c2_x = px_c2*pc[2])
select = function(data)else
return(data)
}final = select(ci_x)
return(final)
}#測試
*****bayes(data,test)

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