R Under development (unstable) (2023-12-09 r85665 ucrt) -- "Unsuffered Consequences"
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> source("RSquared.R")
> 
> # rm(LiblineaR)
> library(LiblineaR)
> 
> set.seed(1)
> N=10
> # Note that 1st record is negative
> df=data.frame(x1 = (1:N)/N*10 + 2*rnorm(N), x2 = (1:N)/N*10 + 2*rnorm(N), x3 = (1:N)/N*10 + 2*rnorm(N))
> df$y.regr = apply(as.matrix(df),1,mean) + 2*rnorm(N)
> df$y.logical = df$y.regr > 5.5
> df$y.int = ifelse(df$y.logical, 1L, -1L)
> df$y.double = as.double(df$y.int)
> df$y.char = as.character(df$y.int)
> df$y.factor = factor(df$y.int)
> df$y.factorRev = factor(df$y.int, levels=rev(levels(df$y.factor)))
> df$y.factorExtra = factor(df$y.int, levels=c(-1,1,99), labels=c("no","yes","maybe"))
> df$y.multiclass = cut(df$y.regr, breaks=c(-99,4,7,99))
> # Expected: good classification performance, negative bias and positive sum of weights 
> 
> regrTargets = "y.regr"
> classifTargets = setdiff(grep("^y",colnames(df), value=TRUE), regrTargets)
> binTargets = setdiff(classifTargets,"y.multiclass")
> 
> testClassif = function(rev,yy,weighted,tt) {
+ 	cat("Testing",rev,yy,weighted,tt,"\n")
+ 	if(rev)
+ 		is=1:nrow(df)
+ 	else
+ 		is=nrow(df):1
+ 	nis = which(!df[is,"y.logical"])
+ 	
+ 	if(weighted) # class weights giving more importance to negative classes
+ 		wi=c("1"=2,"TRUE"=2,"yes"=2, "(7,99]"=1, 
+ 				 "(4,7]"=50,
+ 				 "-1"=100,"FALSE"=100,"no"=100,"(-99,4]"=150)
+ 	else
+ 		wi=NULL
+ 	
+ 	y = df[is,yy]
+ 	x = df[is,1:3]
+ 	m = LiblineaR(x, y, type = tt, wi=wi)
+ 	p = predict(m, newx = x)
+ 	res=c(
+ 		type=tt,
+ 		target=yy,
+ 		weighted=weighted,
+ 		y1 = as.character(y[1]),
+ 		perf=(mean(as.character(y)==as.character(p$predictions))), # >= 0.75
+ 		perfNeg=(mean(as.character(y[nis])==as.character(p$predictions[nis]))), # >= 0.75
+ 		dimW=paste(dim(m$W), collapse = " "),
+ 		sumW=sum(m$W[,1:3]),
+ 		biasW=m$W[1,][["Bias"]],
+ 		classNames=paste(m$ClassNames, collapse = " "),
+ 		yLev=paste(levels(y), collapse=" "),
+ 		predLev=paste(levels(p$predictions), collapse=" "),
+ 		yClass=class(y),
+ 		predClass=class(p$predictions),
+ 		weights=paste(colnames(m$W),"=",round(m$W[1,],3),collapse = " ; ")
+ 	)
+ 	
+ 	#table(true=as.character(y),pred=as.character(p$predictions))
+ 	
+ 	return(res)
+ }
> 
> testRegr = function(rev,yy,tt) {
+ 	cat("Testing",rev,yy,tt,"\n")
+ 	
+ 	if(rev)
+ 		is=1:nrow(df)
+ 	else
+ 		is=nrow(df):1
+ 	
+ 	y = df[is,yy]
+ 	x = df[is,1:3]
+ 	m = LiblineaR(x, y, type = tt, svr_eps=.1)
+ 	p = predict(m, newx = x)
+ 	res=c(
+ 		type=tt,
+ 		target=yy,
+ 		weighted=FALSE,
+ 		y1 = as.character(y[1]),
+ 		perf=RSquared(p$predictions, y), # >= 0.75
+ 		perfNeg=0,
+ 		dimW=paste(dim(m$W), collapse = " "),
+ 		sumW=sum(m$W[,1:3]),
+ 		biasW=m$W[1,][["Bias"]],
+ 		classNames=paste(m$ClassNames, collapse = " "),
+ 		yLev=paste(levels(y), collapse=" "),
+ 		predLev=paste(levels(p$predictions), collapse=" "),
+ 		yClass=class(y),
+ 		predClass=class(p$predictions),
+ 		weights=paste(colnames(m$W),"=",round(m$W[1,],3),collapse = " ; ")
+ 	)
+ 	
+ 	return(res)
+ }
> 
> 
> allRes=NULL
> for(tt in 0:7) {
+ 	for(weighted in c(FALSE,TRUE)) {
+ 		for(rev in c(FALSE,TRUE)) {
+ 			for (yy in classifTargets) {
+ 				res = testClassif(rev,yy,weighted,tt)
+ 				allRes=rbind(allRes,res)
+ 			}
+ 		}
+ 	}
+ }
Testing FALSE y.logical FALSE 0 
Testing FALSE y.int FALSE 0 
Testing FALSE y.double FALSE 0 
Testing FALSE y.char FALSE 0 
Testing FALSE y.factor FALSE 0 
Testing FALSE y.factorRev FALSE 0 
Testing FALSE y.factorExtra FALSE 0 
Testing FALSE y.multiclass FALSE 0 
Testing TRUE y.logical FALSE 0 
Testing TRUE y.int FALSE 0 
Testing TRUE y.double FALSE 0 
Testing TRUE y.char FALSE 0 
Testing TRUE y.factor FALSE 0 
Testing TRUE y.factorRev FALSE 0 
Testing TRUE y.factorExtra FALSE 0 
Testing TRUE y.multiclass FALSE 0 
Testing FALSE y.logical TRUE 0 
Testing FALSE y.int TRUE 0 
Testing FALSE y.double TRUE 0 
Testing FALSE y.char TRUE 0 
Testing FALSE y.factor TRUE 0 
Testing FALSE y.factorRev TRUE 0 
Testing FALSE y.factorExtra TRUE 0 
Testing FALSE y.multiclass TRUE 0 
Testing TRUE y.logical TRUE 0 
Testing TRUE y.int TRUE 0 
Testing TRUE y.double TRUE 0 
Testing TRUE y.char TRUE 0 
Testing TRUE y.factor TRUE 0 
Testing TRUE y.factorRev TRUE 0 
Testing TRUE y.factorExtra TRUE 0 
Testing TRUE y.multiclass TRUE 0 
Testing FALSE y.logical FALSE 1 
Testing FALSE y.int FALSE 1 
Testing FALSE y.double FALSE 1 
Testing FALSE y.char FALSE 1 
Testing FALSE y.factor FALSE 1 
Testing FALSE y.factorRev FALSE 1 
Testing FALSE y.factorExtra FALSE 1 
Testing FALSE y.multiclass FALSE 1 
Testing TRUE y.logical FALSE 1 
Testing TRUE y.int FALSE 1 
Testing TRUE y.double FALSE 1 
Testing TRUE y.char FALSE 1 
Testing TRUE y.factor FALSE 1 
Testing TRUE y.factorRev FALSE 1 
Testing TRUE y.factorExtra FALSE 1 
Testing TRUE y.multiclass FALSE 1 
Testing FALSE y.logical TRUE 1 
Testing FALSE y.int TRUE 1 
Testing FALSE y.double TRUE 1 
Testing FALSE y.char TRUE 1 
Testing FALSE y.factor TRUE 1 
Testing FALSE y.factorRev TRUE 1 
Testing FALSE y.factorExtra TRUE 1 
Testing FALSE y.multiclass TRUE 1 
Testing TRUE y.logical TRUE 1 
Testing TRUE y.int TRUE 1 
Testing TRUE y.double TRUE 1 
Testing TRUE y.char TRUE 1 
Testing TRUE y.factor TRUE 1 
Testing TRUE y.factorRev TRUE 1 
Testing TRUE y.factorExtra TRUE 1 
Testing TRUE y.multiclass TRUE 1 
Testing FALSE y.logical FALSE 2 
Testing FALSE y.int FALSE 2 
Testing FALSE y.double FALSE 2 
Testing FALSE y.char FALSE 2 
Testing FALSE y.factor FALSE 2 
Testing FALSE y.factorRev FALSE 2 
Testing FALSE y.factorExtra FALSE 2 
Testing FALSE y.multiclass FALSE 2 
Testing TRUE y.logical FALSE 2 
Testing TRUE y.int FALSE 2 
Testing TRUE y.double FALSE 2 
Testing TRUE y.char FALSE 2 
Testing TRUE y.factor FALSE 2 
Testing TRUE y.factorRev FALSE 2 
Testing TRUE y.factorExtra FALSE 2 
Testing TRUE y.multiclass FALSE 2 
Testing FALSE y.logical TRUE 2 
Testing FALSE y.int TRUE 2 
Testing FALSE y.double TRUE 2 
Testing FALSE y.char TRUE 2 
Testing FALSE y.factor TRUE 2 
Testing FALSE y.factorRev TRUE 2 
Testing FALSE y.factorExtra TRUE 2 
Testing FALSE y.multiclass TRUE 2 
Testing TRUE y.logical TRUE 2 
Testing TRUE y.int TRUE 2 
Testing TRUE y.double TRUE 2 
Testing TRUE y.char TRUE 2 
Testing TRUE y.factor TRUE 2 
Testing TRUE y.factorRev TRUE 2 
Testing TRUE y.factorExtra TRUE 2 
Testing TRUE y.multiclass TRUE 2 
Testing FALSE y.logical FALSE 3 
Testing FALSE y.int FALSE 3 
Testing FALSE y.double FALSE 3 
Testing FALSE y.char FALSE 3 
Testing FALSE y.factor FALSE 3 
Testing FALSE y.factorRev FALSE 3 
Testing FALSE y.factorExtra FALSE 3 
Testing FALSE y.multiclass FALSE 3 
Testing TRUE y.logical FALSE 3 
Testing TRUE y.int FALSE 3 
Testing TRUE y.double FALSE 3 
Testing TRUE y.char FALSE 3 
Testing TRUE y.factor FALSE 3 
Testing TRUE y.factorRev FALSE 3 
Testing TRUE y.factorExtra FALSE 3 
Testing TRUE y.multiclass FALSE 3 
Testing FALSE y.logical TRUE 3 
Testing FALSE y.int TRUE 3 
Testing FALSE y.double TRUE 3 
Testing FALSE y.char TRUE 3 
Testing FALSE y.factor TRUE 3 
Testing FALSE y.factorRev TRUE 3 
Testing FALSE y.factorExtra TRUE 3 
Testing FALSE y.multiclass TRUE 3 
Testing TRUE y.logical TRUE 3 
Testing TRUE y.int TRUE 3 
Testing TRUE y.double TRUE 3 
Testing TRUE y.char TRUE 3 
Testing TRUE y.factor TRUE 3 
Testing TRUE y.factorRev TRUE 3 
Testing TRUE y.factorExtra TRUE 3 
Testing TRUE y.multiclass TRUE 3 
Testing FALSE y.logical FALSE 4 
Testing FALSE y.int FALSE 4 
Testing FALSE y.double FALSE 4 
Testing FALSE y.char FALSE 4 
Testing FALSE y.factor FALSE 4 
Testing FALSE y.factorRev FALSE 4 
Testing FALSE y.factorExtra FALSE 4 
Testing FALSE y.multiclass FALSE 4 
Testing TRUE y.logical FALSE 4 
Testing TRUE y.int FALSE 4 
Testing TRUE y.double FALSE 4 
Testing TRUE y.char FALSE 4 
Testing TRUE y.factor FALSE 4 
Testing TRUE y.factorRev FALSE 4 
Testing TRUE y.factorExtra FALSE 4 
Testing TRUE y.multiclass FALSE 4 
Testing FALSE y.logical TRUE 4 
Testing FALSE y.int TRUE 4 
Testing FALSE y.double TRUE 4 
Testing FALSE y.char TRUE 4 
Testing FALSE y.factor TRUE 4 
Testing FALSE y.factorRev TRUE 4 
Testing FALSE y.factorExtra TRUE 4 
Testing FALSE y.multiclass TRUE 4 
Testing TRUE y.logical TRUE 4 
Testing TRUE y.int TRUE 4 
Testing TRUE y.double TRUE 4 
Testing TRUE y.char TRUE 4 
Testing TRUE y.factor TRUE 4 
Testing TRUE y.factorRev TRUE 4 
Testing TRUE y.factorExtra TRUE 4 
Testing TRUE y.multiclass TRUE 4 
Testing FALSE y.logical FALSE 5 
Testing FALSE y.int FALSE 5 
Testing FALSE y.double FALSE 5 
Testing FALSE y.char FALSE 5 
Testing FALSE y.factor FALSE 5 
Testing FALSE y.factorRev FALSE 5 
Testing FALSE y.factorExtra FALSE 5 
Testing FALSE y.multiclass FALSE 5 
Testing TRUE y.logical FALSE 5 
Testing TRUE y.int FALSE 5 
Testing TRUE y.double FALSE 5 
Testing TRUE y.char FALSE 5 
Testing TRUE y.factor FALSE 5 
Testing TRUE y.factorRev FALSE 5 
Testing TRUE y.factorExtra FALSE 5 
Testing TRUE y.multiclass FALSE 5 
Testing FALSE y.logical TRUE 5 
Testing FALSE y.int TRUE 5 
Testing FALSE y.double TRUE 5 
Testing FALSE y.char TRUE 5 
Testing FALSE y.factor TRUE 5 
Testing FALSE y.factorRev TRUE 5 
Testing FALSE y.factorExtra TRUE 5 
Testing FALSE y.multiclass TRUE 5 
Testing TRUE y.logical TRUE 5 
Testing TRUE y.int TRUE 5 
Testing TRUE y.double TRUE 5 
Testing TRUE y.char TRUE 5 
Testing TRUE y.factor TRUE 5 
Testing TRUE y.factorRev TRUE 5 
Testing TRUE y.factorExtra TRUE 5 
Testing TRUE y.multiclass TRUE 5 
Testing FALSE y.logical FALSE 6 
Testing FALSE y.int FALSE 6 
Testing FALSE y.double FALSE 6 
Testing FALSE y.char FALSE 6 
Testing FALSE y.factor FALSE 6 
Testing FALSE y.factorRev FALSE 6 
Testing FALSE y.factorExtra FALSE 6 
Testing FALSE y.multiclass FALSE 6 
Testing TRUE y.logical FALSE 6 
Testing TRUE y.int FALSE 6 
Testing TRUE y.double FALSE 6 
Testing TRUE y.char FALSE 6 
Testing TRUE y.factor FALSE 6 
Testing TRUE y.factorRev FALSE 6 
Testing TRUE y.factorExtra FALSE 6 
Testing TRUE y.multiclass FALSE 6 
Testing FALSE y.logical TRUE 6 
Testing FALSE y.int TRUE 6 
Testing FALSE y.double TRUE 6 
Testing FALSE y.char TRUE 6 
Testing FALSE y.factor TRUE 6 
Testing FALSE y.factorRev TRUE 6 
Testing FALSE y.factorExtra TRUE 6 
Testing FALSE y.multiclass TRUE 6 
Testing TRUE y.logical TRUE 6 
Testing TRUE y.int TRUE 6 
Testing TRUE y.double TRUE 6 
Testing TRUE y.char TRUE 6 
Testing TRUE y.factor TRUE 6 
Testing TRUE y.factorRev TRUE 6 
Testing TRUE y.factorExtra TRUE 6 
Testing TRUE y.multiclass TRUE 6 
Testing FALSE y.logical FALSE 7 
Testing FALSE y.int FALSE 7 
Testing FALSE y.double FALSE 7 
Testing FALSE y.char FALSE 7 
Testing FALSE y.factor FALSE 7 
Testing FALSE y.factorRev FALSE 7 
Testing FALSE y.factorExtra FALSE 7 
Testing FALSE y.multiclass FALSE 7 
Testing TRUE y.logical FALSE 7 
Testing TRUE y.int FALSE 7 
Testing TRUE y.double FALSE 7 
Testing TRUE y.char FALSE 7 
Testing TRUE y.factor FALSE 7 
Testing TRUE y.factorRev FALSE 7 
Testing TRUE y.factorExtra FALSE 7 
Testing TRUE y.multiclass FALSE 7 
Testing FALSE y.logical TRUE 7 
Testing FALSE y.int TRUE 7 
Testing FALSE y.double TRUE 7 
Testing FALSE y.char TRUE 7 
Testing FALSE y.factor TRUE 7 
Testing FALSE y.factorRev TRUE 7 
Testing FALSE y.factorExtra TRUE 7 
Testing FALSE y.multiclass TRUE 7 
Testing TRUE y.logical TRUE 7 
Testing TRUE y.int TRUE 7 
Testing TRUE y.double TRUE 7 
Testing TRUE y.char TRUE 7 
Testing TRUE y.factor TRUE 7 
Testing TRUE y.factorRev TRUE 7 
Testing TRUE y.factorExtra TRUE 7 
Testing TRUE y.multiclass TRUE 7 
> 
> for(tt in 11:13) {
+ 	for(rev in c(FALSE,TRUE)) {
+ 		for (yy in regrTargets) {
+ 			res = testRegr(rev,yy,tt)
+ 			allRes=rbind(allRes,res)
+ 		}
+ 	}
+ }
Testing FALSE y.regr 11 
Testing TRUE y.regr 11 
Testing FALSE y.regr 12 
Testing TRUE y.regr 12 
Testing FALSE y.regr 13 
Testing TRUE y.regr 13 
> 
> allRes = as.data.frame(allRes,stringsAsFactors = F)
> # Simple tests
> allRes$dimOK=(allRes$type=="4" | allRes$target=="y.multiclass" | allRes$dimW=="1 4")
> allRes$perfOK=(allRes$target=="y.multiclass" & allRes$perf>=.6 | 
+ 							 	ifelse(allRes$weighted, allRes$perfNeg>=.9, allRes$perf>=.75))
> allRes$sumOK=(!allRes$target%in%c("y.int","y.double") | allRes$type=="4" | as.numeric(allRes$sumW)>0)
> allRes$biasOK=(!allRes$target%in%c("y.int","y.double") | allRes$type=="4" | as.numeric(allRes$biasW)<0)
> allRes$levelsOK=(allRes$target%in%c("y.char","y.double") | (allRes$yLev==allRes$predLev & allRes$yClass==allRes$predClass))
> 
> # View(allRes)
> # library(reshape2)
> # print(dcast(allRes, dimOK + perfOK + levelsOK + sumOK + biasOK ~ .))
> 
> #===============================================================================
> # Testing sparse matrices of various formats
> 
> # Sparsifying the iris dataset:
> iS=apply(iris[,1:4],2,function(a){a[a<quantile(a,probs=c(0.25))]=0;return(a)})
> y=iris[,5]
> 
> # Sparse matrix of class matrix.csr, matrix.csc, matrix.coo from SparseM package :
> if(require(SparseM)){
+   cat("Testing sparse matrices of class matrix.csr from package SparseM.\n")
+   irisSparse<-as.matrix.csr(iS)
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross = 5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+   cat("Testing sparse matrices of class matrix.csc from package SparseM.\n")
+   irisSparse<-as.matrix.csc(iS)
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross = 5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+   cat("Testing sparse matrices of class matrix.coo from package SparseM.\n")
+   irisSparse<-as.matrix.coo(iS)
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross = 5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+ }
Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

Testing sparse matrices of class matrix.csr from package SparseM.
Accuracy: 0.78 
Testing sparse matrices of class matrix.csc from package SparseM.
Accuracy: 0.7333333 
Testing sparse matrices of class matrix.coo from package SparseM.
Accuracy: 0.74 
> 
> # Sparse matrix of class dgRMatrix, dgCMatrix, dgTMatrix from Matrix package :
> if(require(Matrix)){
+   cat("Testing sparse matrices of class dgCMatrix from package Matrix.\n")
+   irisSparse<-as(iS,"sparseMatrix")
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross=5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+   cat("Testing sparse matrices of class dgRMatrix from package Matrix.\n")
+   irisSparse<-as(iS,"sparseMatrix")
+   irisSparse<-as(as(irisSparse,"matrix"),"dgRMatrix")
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross=5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+   cat("Testing sparse matrices of class dgTMatrix from package Matrix.\n")
+   irisSparse<-as(iS,"sparseMatrix")
+   irisSparse<-as(as(irisSparse,"matrix"),"dgTMatrix")
+   acc=LiblineaR(data=irisSparse,target=y,type=0,cost=0.1,bias=1,verbose=FALSE,cross=5)
+   cat("Accuracy:",acc,"\n",sep=" ")
+   
+ }
Loading required package: Matrix
Testing sparse matrices of class dgCMatrix from package Matrix.
'as(<matrix>, "dgRMatrix")' is deprecated.
Use 'as(as(as(., "dMatrix"), "generalMatrix"), "RsparseMatrix")' instead.
See help("Deprecated") and help("Matrix-deprecated").
Accuracy: 0.7666667 
Testing sparse matrices of class dgRMatrix from package Matrix.
Accuracy: 0.8 
Testing sparse matrices of class dgTMatrix from package Matrix.
Accuracy: 0.8 
> #' 
> #' #############################################
> 
> proc.time()
   user  system elapsed 
   2.57    0.15    2.70