Use bst_float consistently throughout (#1824)

* Fix various typos

* Add override to functions that are overridden

gcc gives warnings about functions that are being overridden by not
being marked as oveirridden. This fixes it.

* Use bst_float consistently

Use bst_float for all the variables that involve weight,
leaf value, gradient, hessian, gain, loss_chg, predictions,
base_margin, feature values.

In some cases, when due to additions and so on the value can
take a larger value, double is used.

This ensures that type conversions are minimal and reduces loss of
precision.

demo/kaggle-otto/otto_train_pred.R

@@ -8,7 +8,7 @@ test = test[,-1]
 
 y = train[,ncol(train)]
 y = gsub('Class_','',y)
-y = as.integer(y)-1 #xgboost take features in [0,numOfClass)
+y = as.integer(y)-1  # xgboost take features in [0,numOfClass)
 
 x = rbind(train[,-ncol(train)],test)
 x = as.matrix(x)
@@ -22,7 +22,7 @@ param <- list("objective" = "multi:softprob",
               "num_class" = 9,
               "nthread" = 8)
 
-# Run Cross Valication
+# Run Cross Validation
 cv.nround = 50
 bst.cv = xgb.cv(param=param, data = x[trind,], label = y, 
                 nfold = 3, nrounds=cv.nround)