如何在 R 中使用 libSVM(包 e1071)获得概率?
How get probability using libSVM (package e1071) in R?
我试图在 libSVM 中获取概率输出(R 中的 packeage e1071),但我的数据集的输出仅为 TRUE 或 FALSE。
关注代码:
dadosBrutos<-read.csv("Dataset/circle.data",header = FALSE)
svm.modelo <- svm(V3 ~ .,
data=conjuntoTreinamento,
type='C-classification',
probability=TRUE)
#cost=c,
#type='C-classification',
#kernel='linear',
#scale=FALSE,
#verbose=FALSE
svm.predict <- predict(svm.modelo,
subset(conjuntoTreinamento,
select = -V3),
probability=TRUE)
posterior <- as.matrix(svm.predict)
但是,当我使用数据集 Iris 时,概率输出是 % 而不是 class 的名称。
library(e1071)
model <- svm(Species ~ ., data = iris, probability=TRUE)
pred <- predict(model, iris, probability=TRUE)
head(attr(pred, "probabilities"))
# setosa versicolor virginica
# 1 0.9803339 0.01129740 0.008368729
# 2 0.9729193 0.01807053 0.009010195
# 3 0.9790435 0.01192820 0.009028276
# 4 0.9750030 0.01531171 0.009685342
# 5 0.9795183 0.01164689 0.008834838
# 6 0.9740730 0.01679643 0.009130620
谁能帮我理解一下?
您必须从属性中提取它:
attr(svm.predict, "probabilities")
查看:
https://stat.ethz.ch/pipermail/r-help/2006-February/088476.html
我试图在 libSVM 中获取概率输出(R 中的 packeage e1071),但我的数据集的输出仅为 TRUE 或 FALSE。
关注代码:
dadosBrutos<-read.csv("Dataset/circle.data",header = FALSE)
svm.modelo <- svm(V3 ~ .,
data=conjuntoTreinamento,
type='C-classification',
probability=TRUE)
#cost=c,
#type='C-classification',
#kernel='linear',
#scale=FALSE,
#verbose=FALSE
svm.predict <- predict(svm.modelo,
subset(conjuntoTreinamento,
select = -V3),
probability=TRUE)
posterior <- as.matrix(svm.predict)
但是,当我使用数据集 Iris 时,概率输出是 % 而不是 class 的名称。
library(e1071)
model <- svm(Species ~ ., data = iris, probability=TRUE)
pred <- predict(model, iris, probability=TRUE)
head(attr(pred, "probabilities"))
# setosa versicolor virginica
# 1 0.9803339 0.01129740 0.008368729
# 2 0.9729193 0.01807053 0.009010195
# 3 0.9790435 0.01192820 0.009028276
# 4 0.9750030 0.01531171 0.009685342
# 5 0.9795183 0.01164689 0.008834838
# 6 0.9740730 0.01679643 0.009130620
谁能帮我理解一下?
您必须从属性中提取它:
attr(svm.predict, "probabilities")
查看: https://stat.ethz.ch/pipermail/r-help/2006-February/088476.html