added support files for OAF

Demo_XGB_Scoring.py

@@ -0,0 +1,71 @@
+# Load dependency packages
+import sys
+import csv
+import numpy as np
+import pandas as pd
+from xgboost import XGBClassifier, Booster
+import warnings
+
+# pickle will issue a caution warning, if model pickling was done with
+# different library version than used here. The following disables any warnings
+# that might otherwise show in the scriptlog files on the Advanced SQL Engine
+# nodes in this case. Yet, do keep an eye for incompatible pickle versions.
+warnings.filterwarnings('ignore')
+
+# Know your data: You must know in advance the number and data types of the
+# incoming columns from the SQL Engine database!
+# For this script, the input expected format is:
+colNames = ['txn_id',
+ 'txn_type_CASH_OUT',
+ 'txn_type_CASH_IN',
+ 'txn_type_TRANSFER',
+ 'txn_type_DEBIT',
+ 'txn_type_PAYMENT',
+ 'txn_type_other',
+ 'amount',
+ 'oldbalanceOrig',
+ 'newbalanceOrig',
+ 'oldbalanceDest',
+ 'newbalanceDest',
+ 'isFraud']
+
+
+
+model = XGBClassifier()
+booster = Booster()
+booster.load_model('xgb_model')
+model._Booster = booster
+
+
+d = csv.DictReader(sys.stdin.readlines(), fieldnames = colNames)
+
+df = pd.DataFrame(d, columns = colNames)
+
+# Use try...except to produce an error if something goes wrong in the try block
+try:
+    # Exit gracefully if DataFrame is empty
+    if df.empty:
+        sys.exit()
+
+    # Specify the rows to be scored by the model and call the predictor.
+    X_test = df[['txn_type_CASH_OUT', 'txn_type_CASH_IN','txn_type_TRANSFER', 'txn_type_DEBIT','txn_type_PAYMENT', 'txn_type_other','amount','oldbalanceOrig', 'newbalanceOrig','oldbalanceDest', 'newbalanceDest']].astype(float)
+
+    y_prob = model.predict_proba(X_test)
+    df[['prob_0', 'prob_1']] = y_prob
+
+    y_pred = model.predict(X_test)
+    df['prediction'] = y_pred
+
+    # Export results to the Database through standard output.
+    for index, value in df.iterrows():
+        my_str = str(value['txn_id']) + ',' + str(value['prob_0']) + ',' + str(value['prob_1']) + ',' + str(value['prediction']) + ',' + str(value['isFraud'])
+        print(my_str)
+
+
+except (SystemExit):
+    # Skip exception if system exit requested in try block
+    pass
+except:    # Specify in standard error any other error encountered
+    print("Script Failure :", sys.exc_info()[0], file=sys.stderr)
+    raise
+    sys.exit()