glmnetとbrnnパッケージの使い方を学んでいます。次のコードを検討してください。
library(RODBC)
library(brnn)
library(glmnet)
memory.limit(size = 4000)
z <-odbcConnect("mydb") # database with Access queries and tables
# import the data
f5 <- sqlFetch(z,"my_qry")
# head(f5)
# check for 'NA'
sum(is.na(f5))
# choose a 'locn', up to 16 of variable 'locn' are present
f6 <- subset(f5, locn == "mm")
# dim(f6)
# use glmnet to identify possible iv's
training_xnm <- f6[,1:52] # training data
xnm <- as.matrix(training_xnm)
y <- f6[,54] # response
fit.nm <- glmnet(xnm,y, family="binomial", alpha=0.6, nlambda=1000,standardize=TRUE,maxit=100000)
# print(fit.nm)
# cross validation for glmnet to determine a good lambda value
cv.fit.nm <- cv.glmnet(xnm, y)
# have a look at the 'min' and '1se' lambda values
cv.fit.nm$lambda.min
cv.fit.nm$lambda.1se
# returned $lambda.min of 0.002906279, $lambda.1se of 2.587214
# for testing purposes I choose a value between 'min' and '1se'
mid.lambda.nm = (cv.fit.nm$lambda.min + cv.fit.nm$lambda.1se)/2
print(coef(fit.nm, s = mid.lambda.nm)) # 8 iv's retained
# I then manually inspect the data frame and enter the column index for each of the iv's
# these iv's will be the input to my 'brnn' neural nets
cols <- c(1, 3, 6, 8, 11, 20, 25, 38) # column indices of useful iv's
# brnn creation: only one shown but this step will be repeated
# take a 85% sample from data frame
ridxs <- sample(1:nrow(f6), floor(0.85*nrow(f6)) ) # row id's
f6train <- f6[ridxs,] # the resultant data frame of 85%
f6train <-f6train[,cols] # 'cols' as chosen above
# For the 'brnn' phase response is a binary value, 'fin'
# and predictors are the 8 iv's found earlier
out = brnn( fin ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8, data=f6train, neurons=3,normalize=TRUE, epochs=500, verbose=FALSE)
#summary(out)
# see how well the net predicts the training cases
pred <- predict(out)
上記のスクリプトは正常に実行されます。
私の質問は次のとおりです。上記のスクリプトを自動化して、 のさまざまな値に対して実行するにはどうすればよいですlocnかcols <- c(1, 3, 6, 8, 11, 20, 25, 38) # column indices of useful iv's。現在、これを手動で行うことができますがlocn、たとえば、のさまざまな値に対して一般的な方法でこれを行う方法がわかりません
locn.list <- c("am", "bm", "cm", "dm", "em")
for(j in 1:5) {
this.locn <- locn.list[j]
# run the above script
}