[R] enforce lintr checks (fixes #8012) (#8613)

demo/kaggle-higgs/speedtest.R

@@ -26,7 +26,7 @@ print(paste("weight statistics: wpos=", sumwpos, "wneg=", sumwneg, "ratio=", sum
 
 xgboost.time <- list()
 threads <- c(1, 2, 4, 8, 16)
-for (i in 1:length(threads)){
+for (i in seq_along(threads)){
   thread <- threads[i]
   xgboost.time[[i]] <- system.time({
     xgmat <- xgb.DMatrix(data, label = label, weight = weight, missing = -999.0)

demo/kaggle-otto/otto_train_pred.R

@@ -13,7 +13,7 @@ y <- as.integer(y) - 1  # xgboost take features in [0,numOfClass)
 x <- rbind(train[, -ncol(train)], test)
 x <- as.matrix(x)
 x <- matrix(as.numeric(x), nrow(x), ncol(x))
-trind <- 1:length(y)
+trind <- seq_along(y)
 teind <- (nrow(train) + 1):nrow(x)
 
 # Set necessary parameter
@@ -43,6 +43,6 @@ pred <- t(pred)
 
 # Output submission
 pred <- format(pred, digits = 2, scientific = FALSE) # shrink the size of submission
-pred <- data.frame(1:nrow(pred), pred)
+pred <- data.frame(seq_len(nrow(pred)), pred)
 names(pred) <- c('id', paste0('Class_', 1:9))
 write.csv(pred, file = 'submission.csv', quote = FALSE, row.names = FALSE)

demo/kaggle-otto/understandingXGBoostModel.Rmd

@@ -30,7 +30,7 @@ require(xgboost)
 require(methods)
 require(data.table)
 require(magrittr)
-train <- fread('data/train.csv', header = T, stringsAsFactors = FALSE)
+train <- fread('data/train.csv', header = TRUE, stringsAsFactors = FALSE)
 test <- fread('data/test.csv', header = TRUE, stringsAsFactors = FALSE)
 ```
 > `magrittr` and `data.table` are here to make the code cleaner and much more rapid.