addFeatures {featurefinder}

addFeatures

Description

Use the results of findFeatures to append promising features to a dataframe for further testing

Usage

addFeatures(df, path, prefix)

Arguments

df

A dataframe

path

A string

prefix

A list of trees generated by saveTree

Value

A dataframe with extra features appended

Examples

require(featurefinder)
data(futuresdata)
data=futuresdata
data$SMIfactor=paste("smi",as.matrix(data$SMIfactor),sep="")
n=length(data$DAX)
nn=floor(length(data$DAX)/2)

# Can we predict the relative movement of DAX and SMI?
data$y=data$DAX*0 # initialise the target to 0
data$y[1:(n-1)]=((data$DAX[2:n])-(data$DAX[1:(n-1)]))/
  (data$DAX[1:(n-1)])-(data$SMI[2:n]-(data$SMI[1:(n-1)]))/(data$SMI[1:(n-1)])

# Fit a simple model
thismodel=lm(formula=y ~ .,data=data)
expected=predict(thismodel,data)
actual=data$y
residual=actual-expected
data=cbind(data,expected, actual, residual)

CSVPath=tempdir()
fcsv=paste(CSVPath,"/futuresdata.csv",sep="")
write.csv(data[(nn+1):(length(data$y)),],file=fcsv,row.names=FALSE)
exclusionVars="\"residual\",\"expected\", \"actual\",\"y\""
factorToNumericList=c()

# Now the dataset is prepared, try to find new features
tempDir=findFeatures(outputPath="NoPath", fcsv, exclusionVars,
factorToNumericList,                     
treeGenerationMinBucket=50,
treeSummaryMinBucket=20,
useSubDir=FALSE)  
         
newfeat1=((data$SMIfactor==0) & (data$CAC < 2253) & (data$CAC< 1998) & (data$CAC>=1882)) * 1.0
newfeat2=((data$SMIfactor==1) & (data$SMI < 7837) & (data$SMI >= 7499)) * 1.0
newfeatures=cbind(newfeat1, newfeat2) # create columns for the newly found features
datanew=cbind(data,newfeatures)
thismodel=lm(formula=y ~ .,data=datanew)
expectednew=predict(thismodel,datanew)

requireNamespace("Metrics")
OriginalRMSE = Metrics::rmse(data$y,expected)
NewRMSE = Metrics::rmse(data$y,expectednew)

print(paste("OriginalRMSE = ",OriginalRMSE))
print(paste("NewRMSE = ",NewRMSE))

# Append new features to a dataframe automatically
dataWithNewFeatures = addFeatures(df=data, path=tempDir, prefix="auto_")
head(df)