库Gmum.r
不支持SVR(支持向量回归)?
library(RODBC)
sqlConnString = "driver={SQL
Server};server=140.136.156.36;database=RealEstate_final;uid={sa};pwd=
{Root1234}"
conn <- odbcDriverConnect(sqlConnString)
EstateNew <- sqlQuery(conn, " SELECT * FROM EstateNew ")
#head(FraudDF1, 5)
odbcClose(conn)
expectcol&lt; -delete neednt column
expectcol <-
c("ID","Address","RealAddr","NonUrbanZone","NonUrbanLand","Aport_ID"
,"ParkB_ID","Univ_ID","ParkR_ID","Rzone_ID","Rzone_CentDistance"
,"Flood_ID","Flood_CentDistance","SoilLiq_ID","MRT_ID","MRT_OrderS"
,"MRT_LID","MRT_OrderLS","Fway_ID","Fway_OrderS","Fway_LID","Fway_OrderLS"
,"TRA_ID","TRA_OrderS","TRA_LID","TRA_OrderLS","THSR_ID","THSR_OrderS"
,"THSR_LID","THSR_OrderLS","River_ID","River_OrderLS","Fault_ID"
,"Fault_OrderLS","A001_ID","A002_ID","A003_ID","A004_ID","E001_ID"
,"E002_ID","L001_ID","L002_ID","L003_ID","L004_ID","B001_ID","B002_ID"
,"B003_ID","Lng_X","Lat_Y","Section","Rzone","ParkingType","ParkingArea"
,"ParkingPrice","ParkingLot","TotalPrice")
#EstateNew$TransDate<-as.Date(EstateNew$TransDate)
#EstateNew$HouseDate<-as.Date(EstateNew$HouseDate)
#,"TransDate","HouseDate"
#將expectcol剃除
tempdata <- EstateNew[,!names(EstateNew) %in% expectcol,drop=FALSE]
选择部门
tempdata<-subset(tempdata,
tempdata$TransType==3 & tempdata$ZoneUse==2
& tempdata$HouseUse==1 & tempdata$HouseType==1)
删除数据
sum(complete.cases(tempdata))
tempdata <- na.omit(tempdata)
家庭年龄
transyear<-as.numeric(substr(tempdata$TransDate, 1, 4))
houseyear<-as.numeric(substr(tempdata$HouseDate, 1, 4))
age_frame <- data.frame(HouseAge = transyear-houseyear)
tempdata<-cbind(tempdata,age_frame)
expectcol <-c("TransDate","HouseDate")
tempdata <- tempdata[,!names(tempdata) %in% expectcol,drop=FALSE]
特征选择值
finaldata<-subset(tempdata,
select = c("Lng","Pcode5_ID","TransFloor","HouseArea" ,"Lat","River_LineDistance","A002_Distance","ParkB_Distance"
,"MRT_LineDistance","LandArea","A003_Distance"
,"L002_Distance","L003_Distance"
,"HouseAge","Price"))
index <- 1:nrow(finaldata)
np = ceiling(1*nrow(finaldata))
test.index = sample(1:nrow(finaldata),np)
#testdata = finaldata[test.index,]
traindata = finaldata[test.index,]
SVR
library(gmum.r)
svm.rbf <- SVM(formula=Price~., data=traindata, core="libsvm", kernel="rbf",
C=1.0, gamma=0.5)
火车支持向量回归模型有一些误区
WARNING_LEVEL:使用-h 0可能会更快完成优化,#iter = 1024