1.抽取训练集和测试集
序号抽取
法1.sample(1:dim(iris)[1],0.7*dim(iris)[1])
法2. sample(2,nrow(iris),prob = c(0.7,0.3),replace = TRUE)方法很巧妙
2.建立模型
iris_svm_model = svm(Species~.,data = iris.train1)
summary(iris_svm_model)
y = iris.test1[,5]
3.预测
iris_test1_pred = predict(iris_svm_model,iris.test1[,-5])
模型+要预测的内容
4.对比
iris_table = table(pred = iris_test1_pred, true = y)
iris_table
5.代码
library(MASS)
library(e1071)
install.packages('attach')
data("iris")
head(iris)
attach(iris)
temp = sample(1:dim(iris)[1],0.7*dim(iris)[1])
iris.train1 = iris[temp,]
iris.test1 = iris[-temp,]
iris_svm_model = svm(Species~.,data = iris.train1)
summary(iris_svm_model)
y = iris.test1[,5]
iris_test1_pred = predict(iris_svm_model,iris.test1[,-5])
iris_table = table(pred = iris_test1_pred, true = y)
iris_table