问题描述
发布评估游侠。两者都无法对数据进行子集化（想要rf.trnprob的第一列）
rangermodel= ranger(outcome~.,data=traindata,num.trees=200,probability=TRUE)
rf.trnprob= predict(rangerModel,traindata,type='prob')
trainscore <- subset(traindata,select=c("outcome"))
trainscore$score<-rf.trnprob[,1]
错误：
尺寸错误
table(pred = rf.trbprob,true=traindata$outcome)
错误：
所有参数的长度必须相同
解决方法
似乎错误地调用了class Solution {
public static void main(String[] args) {
/*
* 5235 and 4068 is OK
* 5235 and 5339 is OK
* 5235 and 2553 is OK
* 5235 and 5236 is NOT OK
* 5325 and 5235 is NOT OK (permutation)
*/
// threshold is the maximum number of digits that can be the same
// while the pin1,pin2 are distant enough; in this case 2
int threshold = 2;
int pinLength = 4;
System.out.println(areDistant(5235,4068,threshold,pinLength));
System.out.println(areDistant(5235,5339,2553,5236,pinLength));
System.out.println(areDistant(5325,5235,pinLength));
}
public static boolean areDistant(int pin1,int pin2,int threshold,int pinLength) {
if (isPermutation(pin1,pin2))
return false;
int sameDigits = 0;
int ithDigit1,ithDigit2;
for (int i=0; i<pinLength; i++) {
ithDigit1 = (int) (pin1 / Math.pow(10,i)) % 10;
ithDigit2 = (int) (pin2 / Math.pow(10,i)) % 10;
// System.out.println(ithDigit1);
// System.out.println(ithDigit2);
if ( ithDigit1 == ithDigit2)
sameDigits += 1;
}
return sameDigits <= threshold;
}
private static boolean isPermutation(int pin1,int pin2) {
return false;
// fill the code here
}
}
函数，它应该是predict而不是response。使用示例数据集：
type概率存储在此处，每个类的一列：
library(ranger)
traindata =iris
traindata$Species = factor(as.numeric(traindata$Species=="versicolor"))
rangerModel = ranger(Species~.,data=traindata,probability=TRUE)
rf.trnprob= predict(rangerModel,traindata,response='prob')
但是似乎您想做一个混淆矩阵，因此您可以通过以下方式获得预测：
head(rf.trnprob$predictions)
0 1
[1,] 1.0000000 0.000000000
[2,] 0.9971786 0.002821429
[3,] 1.0000000 0.000000000
[4,] 1.0000000 0.000000000
[5,] 1.0000000 0.000000000
[6,] 1.0000000 0.000000000
然后：
pred = levels(traindata$Species)[max.col(rf.trnprob$predictions)]