def predict_binary()

in src/ppxgboost/PPBooster.py [0:0]

• 5 lines of code
• 3 McCabe index (conditional complexity)

def predict_binary(trees, vector, default_base_score=0.5):
    """
    Prediction on @vector over the @trees
    :param default_base_score: default score is 0.5 (according to the xgboost -- global bias)
    :param trees: list of trees
    :param vector: a list of input vectors
    :return: the prediction values (summation of the values from all the leafs)
    """
    result = []
    for index, row in vector.iterrows():
        # compute the score for all of the input vectors
        result.append(predict_single_input_binary(trees, row))
    # returns result as np array
    return np.array(result)