demo-workspace/scripts/xgboost_starter_script.py [29:59]:
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    args = parser.parse_args()
    
    s3_client = boto3.client("s3")

    data = pd.read_csv(f"{args.train_data_path}/train.csv")
    train = data.drop("fraud", axis=1)
    label = pd.DataFrame(data["fraud"])
    dtrain = xgb.DMatrix(train, label=label)

    params = {"max_depth": args.max_depth, "eta": args.eta, "objective": args.objective}
    num_boost_round = args.num_round
    nfold = args.nfold
    early_stopping_rounds = args.early_stopping_rounds

    cv_results = xgb.cv(
        params=params,
        dtrain=dtrain,
        num_boost_round=num_boost_round,
        nfold=nfold,
        early_stopping_rounds=early_stopping_rounds,
        metrics=("auc"),
        seed=0,
    )

    print(f"[0]#011train-auc:{cv_results.iloc[-1]['train-auc-mean']}")
    print(f"[1]#011validation-auc:{cv_results.iloc[-1]['test-auc-mean']}")

    metrics_data = {
        "binary_classification_metrics": {
            "validation:auc": {
                "value": cv_results.iloc[-1]["test-auc-mean"],
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repos/build_pipeline/scripts/xgboost_starter_script.py [32:62]:
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    args = parser.parse_args()

    s3_client = boto3.client("s3")

    data = pd.read_csv(f"{args.train_data_path}/train.csv")
    train = data.drop("fraud", axis=1)
    label = pd.DataFrame(data["fraud"])
    dtrain = xgb.DMatrix(train, label=label)

    params = {"max_depth": args.max_depth, "eta": args.eta, "objective": args.objective}
    num_boost_round = args.num_round
    nfold = args.nfold
    early_stopping_rounds = args.early_stopping_rounds

    cv_results = xgb.cv(
        params=params,
        dtrain=dtrain,
        num_boost_round=num_boost_round,
        nfold=nfold,
        early_stopping_rounds=early_stopping_rounds,
        metrics=("auc"),
        seed=0,
    )

    print(f"[0]#011train-auc:{cv_results.iloc[-1]['train-auc-mean']}")
    print(f"[1]#011validation-auc:{cv_results.iloc[-1]['test-auc-mean']}")

    metrics_data = {
        "binary_classification_metrics": {
            "validation:auc": {
                "value": cv_results.iloc[-1]["test-auc-mean"],
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