root.matrix（crossprod（process））中的错误：矩阵不是正半确定的

Question

我想扩展RandomForest，以便每个叶子将包含naivebayes回归而不是平均值。在下文中，我首先尝试使用mob()添加linearModel。我收到以下错误：

Error in root.matrix(crossprod(process)) :    matrix is not positive semidefinite

这是我的代码：

require (data.table)
require (party)
set.seed(123)

data1 <- read.csv('https://archive.ics.uci.edu/ml/machine-learning-databases/car/car.data',header = TRUE)
colnames(data1)<-  c("BuyingPrice","Maintenance","NumDoors","NumPersons","BootSpace","Safety","Condition")

# Split into Train and Validation sets
# Training Set : Validation Set = 70 : 30 (random)
set.seed(100)
train <- sample(nrow(data1), 0.7*nrow(data1), replace = FALSE)
TrainSet <- data1[train,]
ValidSet <- data1[-train,]
summary(TrainSet)
summary(ValidSet)

# Create a Random Forest model with default parameters
model1 <- randomForest(Condition ~ ., data = TrainSet, importance = TRUE)
model1

# Fine tuning parameters of Random Forest model
model2 <- randomForest(Condition ~ ., data = TrainSet, ntree = 500, mtry = 6, importance = TRUE)
model2


fmBH <- mob(Condition ~ BuyingPrice +  Maintenance | NumDoors+ NumPersons + BootSpace + Safety ,
            data = TrainSet, model = linearModel)