rank
fun SplitMetric.rank(total: WeightedVarianceResult, pos: List<WeightedVarianceResult>, neg: List<WeightedVarianceResult>, minSamplesSplit: Double, minSamplesLeaf: Double): SplitInfo(source)
Score every candidate split and return the top-2 + index. Splits that don't meet minSamplesLeaf on both sides or minSamplesSplit in total are skipped.