Tree Ensemble

class TreeEnsemble():
    def __init__(self, x, y, n_trees, sample_sz, min_leaf=5):
        np.random.seed(42)
        self.x,self.y,self.sample_sz,self.min_leaf = x,y,sample_sz,min_leaf
        self.trees = [self.create_tree() for i in range(n_trees)]

    def create_tree(self):
        rnd_idxs = np.random.permutation(len(self.y))[:self.sample_sz]
        return DecisionTree(self.x.iloc[rnd_idxs], self.y[rnd_idxs], min_leaf=self.min_leaf)
        
    def predict(self, x):
        return np.mean([t.predict(x) for t in self.trees], axis=0)