Algorithm 1 BestSplitByHistogram Algorithm
1	Input: d: training data, max_depth
2	Input:m: merger fingerprint dimension
3	nodeSet = {0} #tree nodes in current level
4	rowSet = {{0,1,2,...}} #data indices in tree nodes
5	for i = 1 to max_depth
6		for node in nodeSet do
7			usedRows = rowSet[node]
8			for j = 1 to m do
9				H = new Histogram()
10				#Build histogram
11				for k in usedRows do
12					bin = d.s[j][k].bin
13					H[bin].g += d.g[j] #Sum of gradients in each bin
14					H[bin].n += 1 #Sum of samples in each bin
15				Find the best split on histogram H.
16		Update rowSet and nodeSet according to the best split points