Xgboost fit won't recognize my custom eval_metric. Why?

Question

Xgboost fit won't recognize my custom eval_metric. Why?

Gábor B

2021年7月30日 08:55

Do you know why my custom_eval_metric doesn't work? I get the error:

XGBoostError: [07:56:32] C:\Users\Administrator\workspace\xgboost-win64_release_1.4.0\src\metric\metric.cc:49: Unknown metric function custom_eval_metric

def custom_eval_metric(preds, dtrain):
    labels = dtrain.get_label()
    preds = preds.reshape(-1, 3)
    preds_binary = []
    for element in range(0,len(preds)):
        tmp = []
        tmp = preds[element][2]
        preds_binary.append(tmp)
    labels_adj = [0 if x == 1 else x for x in labels]
    labels_adj = [1 if x == 2 else x for x in labels_adj]
    preds_binary = np.asarray([preds_binary])
    labels_adj = np.asarray([labels_adj])
    return 'ndcg score', metrics.ndcg_score(new_items, preds)

clf_xgb_out_of_sample = xgb.XGBClassifier(objective = multi:softmax,
                            num_class=3,
                           seed = 42,
                           n_estimators=2,
                           max_depth = 8,
                            learning_rate = 0.1,
                            gamma = 0.25,
                            colsample_bytree = 0.8,
                            use_label_encoder=False)

clf_xgb_out_of_sample.fit(X_train,
           y_train,
            sample_weight=weights,
           verbose = True,
           early_stopping_rounds = 10,
            eval_metric='custom_eval_metric',
           eval_set = [(X_test, y_test['Target'])])

Topic error-handling classification

Category Data Science

Niklas Riewald · Accepted Answer · 2021年7月30日 08:55

From the documentation:

If a str, should be a built-in evaluation metric to use. See doc/parameter.rst.

...

If callable, a custom evaluation metric. The call signature is func(y_predicted, y_true) where y_true will be a DMatrix object such that you may need to call the get_label method. It must return a str, value pair where the str is a name for the evaluation and value is the value of the evaluation function. The callable custom objective is always minimized.

So you need to pass the function itself instead of a string of the function name

Xgboost fit won't recognize my custom eval_metric. Why?

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