human
Solve the following python programming problem given the following code:
# Not meant for regression!
class rforest:
    #initalizes all the trees and partitions the data.
    def __init__(self, data, labels, numtrees, partition_size, maxdepth=None):
        self.trees = []
        self.data = data
        self.labels = labels
        self.partitions = []
        
        #create partitions
        for i in range(numtrees):
            
            dpart, lpart = zip(*random.sample(list(zip(data,labels)), partition_size))
           
            self.partitions.append((dpart, lpart))
            self.trees.append(dtree(np.array(list(dpart)), np.array(list(lpart)), maxdepth=maxdepth))
        
        
    
    def train(self, bag=0, typetable=None, heuristic=None):
        for tree in self.trees:
            tree.train(bag, typetable, heuristic)
        
    
    #Ensemble voting
    def ensemble(self,x):
        box = {}
        for tree in self.trees:
            vote = tree.classify(x)
            if vote is not None:
                if vote in box:
                    box[vote] += 1
                else:
                    box[vote] = 1
        
        
        return box
    
    def classify(self, x):
        predictions = self.ensemble(x)
        i, m = None, -1
        for pred, votes in predictions.items():
            if votes > m:
                i,m = pred, votes
        
        return i
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python program you requested.

Random Forests
Now we can aggregate our forest fun with random forests who decorolate decision trees and take therir average!