average has to be one of (param0)

Package:

scikit-learn

47032

Exception Class:

ValueError

Raise code

""" e : float or array of shape [n_classes]
        If not ``None``, average the score, else return the score for each
        classes.

    """
    average_options = (None, 'micro', 'macro', 'weighted', 'samples')
    if average not in average_options:
        raise ValueError('average has to be one of {0}'
                         ''.format(average_options))

    y_type = type_of_target(y_true)
    if y_type not in ("binary", "multilabel-indicator"):
        raise ValueError("{0} format is not supported".format(y_type))

    if y_type == "binary":

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Links to the raise (1)

https://github.com/scikit-learn/scikit-learn/blob/c67518350f91072f9d37ed09c5ef7edf555b6cf6/sklearn/metrics/_base.py#L69

Ways to fix

average should be one of the following values.

{'micro', 'samples', 'weighted', 'macro'} or None,

Steps to reproduce the exception:

import numpy as np
from sklearn.metrics import average_precision_score
y_true = np.array([0, 0, 1, 1])
y_scores = np.array([0.1, 0.4, 0.35, 0.8])
result = average_precision_score(y_true, y_scores,average="micr")
print(result)

---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-16-07d5e8a098dc> in <module>()  3 y_true = np.array([0, 0, 1, 1])  4 y_scores = np.array([0.1, 0.4, 0.35, 0.8]) ----> 5 result = average_precision_score(y_true, y_scores,average="micr")  6 print(result) 
/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_ranking.py in average_precision_score(y_true, y_score, average, pos_label, sample_weight)  231 )  232 return _average_binary_score( --> 233 average_precision, y_true, y_score, average, sample_weight=sample_weight  234 )  235  
/usr/local/lib/python3.7/dist-packages/sklearn/metrics/_base.py in _average_binary_score(binary_metric, y_true, y_score, average, sample_weight)  66 average_options = (None, "micro", "macro", "weighted", "samples")  67 if average not in average_options: ---> 68 raise ValueError("average has to be one of {0}".format(average_options))  69   70 y_type = type_of_target(y_true) 
ValueError: average has to be one of (None, 'micro', 'macro', 'weighted', 'samples')

Fixed version of the code:

import numpy as np
from sklearn.metrics import average_precision_score
y_true = np.array([0, 0, 1, 1])
y_scores = np.array([0.1, 0.4, 0.35, 0.8])
result = average_precision_score(y_true, y_scores,average="micro")
print(result)

0.8333333333333333

Mar 29, 2022

kellemnegasi 30.0k

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