add r basic walkthrough

demo/guide-R/basic_walkthrough.R

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+require(xgboost)
+
+dtrain <- xgb.DMatrix('../data/agaricus.txt.train')
+dtest <- xgb.DMatrix('../data/agaricus.txt.test')
+param <- list(max_depth=2,eta=1,silent=1,objective='binary:logistic')
+watchlist <- list(eval = dtest, train = dtrain)
+num_round <- 2
+bst <- xgb.train(param, dtrain, num_round, watchlist)
+preds <- predict(bst, dtest)
+labels <- getinfo(dtest,'label')
+cat('error=', mean(as.numeric(preds>0.5)!=labels),'\n')
+xgb.save(bst, 'xgb.model')
+xgb.dump(bst, 'dump.raw.txt')
+xgb.dump(bst, 'dump.nuce.txt','../data/featmap.txt')
+
+bst2 <- xgb.load('xgb.model')
+preds2 <- predict(bst2,dtest)
+stopifnot(sum((preds-preds2)^2)==0)
+
+
+cat('start running example of build DMatrix from scipy.sparse CSR Matrix\n')
+read.libsvm <- function(fname, maxcol) {
+    content <- readLines(fname)
+    nline <- length(content)
+    label <- numeric(nline)
+    mat <- matrix(0, nline, maxcol + 1)
+    for (i in 1:nline) {
+        arr <- as.vector(strsplit(content[i], " ")[[1]])
+        label[i] <- as.numeric(arr[[1]])
+        for (j in 2:length(arr)) {
+            kv <- strsplit(arr[j], ":")[[1]]
+            # to avoid 0 index
+            findex <- as.integer(kv[1]) + 1
+            fvalue <- as.numeric(kv[2])
+            mat[i, findex] <- fvalue
+        }
+    }
+    mat <- as(mat, "sparseMatrix")
+    return(list(label = label, data = mat))
+}
+csc <- read.libsvm("../data/agaricus.txt.train", 126)
+y <- csc$label
+x <- csc$data
+class(x)
+dtrain <- xgb.DMatrix(x, label = y)
+bst <- xgb.train(param, dtrain, num_round, watchlist)
+
+cat('start running example of build DMatrix from numpy array\n')
+x <- as.matrix(x)
+class(x)
+dtrain <- xgb.DMatrix(x, label = y)
+bst <- xgb.train(param, dtrain, num_round, watchlist)
+