(train_scores: list, validate_scores: list)
return count / len(train_scores)
train/validate scores: predicted scores on train/validate set
train/validate scores: predicted scores on train/validate set
train / validate scores : predicted scores on train / validate set
def compute(train_scores: list, validate_scores: list):
        """
        train/validate scores: predicted scores on train/validate set
        """
        train_scores = np.array(train_scores)
        validate_scores = np.array(validate_scores)
        validate_scores = dict(validate_scores)
        count = 0
        for key, value in train_scores:
            if key in validate_scores.keys() and value != validate_scores.get(key):
                count += 1
        return count / len(train_scores)
def compute ( train_scores : list , validate_scores : list ) : train_scores = np . array ( train_scores ) validate_scores = np . array ( validate_scores ) validate_scores = dict ( validate_scores ) count = 0 for key , value in train_scores : if key in validate_scores . keys ( ) and value != validate_scores . get ( key ) : count += 1 return count / len ( train_scores )