CODEWITHSUNDEEP
pythonoptimizationxgboost
Lesnar
Lesnar

Reputation: 501

Issue with XGboost tuning with Hyperopt- TypeError: 'generator' object has no attribute '__getitem__'

I am testing hyperoptim for parameter tuning of XGboost. I am kind of replicating the code from here- https://www.kaggle.com/eikedehling/tune-and-compare-xgb-lightgbm-rf-with-hyperopt

I am using Python 3 and getting the following error for the code snippet given below. any idea how to resolve this?

def objective(params):
    params = {
        'max_depth': int(params['max_depth']),
        'gamma': "{:.3f}".format(params['gamma']),
        'colsample_bytree': '{:.3f}'.format(params['colsample_bytree']),
    }

    clf = xgb.XGBClassifier(
        n_estimators=50,
        learning_rate=0.1,
        n_jobs=4,
        **params
    )

    score = cross_val_score(clf, train_X, train_Y, scoring=gini_scorer, cv=StratifiedKFold()).mean()
    print("Gini {:.3f} params {}".format(score, params))
    return score

space = {
    'max_depth': hp.quniform('max_depth', 2, 8, 1),
    'colsample_bytree': hp.uniform('colsample_bytree', 0.3, 1.0),
    'gamma': hp.uniform('gamma', 0.0, 0.5),
}

best = fmin(fn=objective,
            space=space,
            algo=tpe.suggest,
            max_evals=10)

Traceback (most recent call last): File "", line 4, in File "/anaconda3/envs/py27/lib/python2.7/site-packages/hyperopt/fmin.py", line 314, in fmin pass_expr_memo_ctrl=pass_expr_memo_ctrl) File "/anaconda3/envs/py27/lib/python2.7/site-packages/hyperopt/base.py", line 786, in init pyll.toposort(self.expr) File "/anaconda3/envs/py27/lib/python2.7/site-packages/hyperopt/pyll/base.py", line 715, in toposort assert order[-1] == expr

TypeError: 'generator' object has no attribute 'getitem'

Upvotes: 1

Views: 760

Answers (1)

Lesnar
Lesnar

Reputation: 501

Resolved! The issue is incompatibility of Hyperopt with networkxx2. One needs to downgrade to "networkxx1.11".

Upvotes: 1

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