Hyperopt Ensemble Search function

ensemble_search.py

def ensemble_search(params):
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=22)

    model = EnsembleModel(params)

    evaluation = [(X_test, y_test)]

    model.fit(X_train, y_train,
              eval_set=evaluation,
              early_stopping_rounds=100, verbose=False)

    val_preds = model.predict(X_test)
    
    fpr, tpr, thresholds = roc_curve(y_test, val_preds, pos_label = 1)
    auc_score = auc(fpr, tpr)

    neg_auc_score = -1 * auc_score

    return {"loss": neg_auc_score, "status": STATUS_OK}