R：使用大內存庫進行randomForest分類

Question

任何人都可以使用randomForest和bigmemory庫設置分類（而不是迴歸）。我知道不能使用'公式方法'，我們不得不求助於'x =預測器，y =響應方法'。看起來大內存庫不能處理具有分類值的響應向量它是一個矩陣，畢竟）在我的情況下，我有兩個級別，都表示爲字符

根據bigmemory文檔...「一個數據幀將字符向量轉換爲因子，然後所有因素轉換爲數字因子水平」

任何建議的解決辦法得到隨機森林分類與bigmemory工作？

#EXAMPLE to problem 
library(randomForest) 
library(bigmemory) 
# Removing any extra objects from my workspace (just in case) 
rm(list=ls()) 

#first small matrix 
small.mat <- matrix(sample(0:1,5000,replace = TRUE),1000,5) 
colnames(small.mat) <- paste("V",1:5,sep = "") 
small.mat[,5] <- as.factor(small.mat[,5]) 
small.rf <- randomForest(V5 ~ .,data = small.mat, mtry=2, do.trace=100) 
print(small.rf) 
small.result <- matrix(0,1000,1) 
small.result <- predict(small.rf, data=small.mat[,-5]) 

#now small dataframe Works! 
small.mat <- matrix(sample(0:1,5000,replace = TRUE),1000,5) 
colnames(small.mat) <- paste("V",1:5,sep = "") 
small.data <- as.data.frame(small.mat) 

small.data[,5] <- as.factor(small.data[,5]) 
small.rf <- randomForest(V5 ~ .,data = small.data, mtry=2, do.trace=100) 
print(small.rf) 
small.result <- matrix(0,1000,1) 
small.result <- predict(small.rf, data=small.data[,-5]) 


#then big matrix Classification Does NOT Work :-(
#----------------****************************---- 
big.mat <- as.big.matrix(small.mat, type = "integer") 
#Line below throws error, "cannot coerce class 'structure("big.matrix", package = "bigmemory")' into a data.frame" 
big.rf <- randomForest(V5~.,data = big.mat, do.trace=10) 

#Runs without error but only regression 
big.rf <- randomForest(x = big.mat[,-5], y = big.mat[,5], mtry=2, do.trace=100) 
print(big.rf) 
big.result <- matrix(0,1000,1) 
big.result <- predict(big.rf, data=big.mat[,-5]) 

Answer 1

bigrf包可能會有所幫助。目前，它支持使用有限數量的功能進行分類。