add Scorecard

Signed-off-by: weiwee <[email protected]>

Author: sagewe

fate-serving-federatedml/src/main/java/com/webank/ai/fate/serving/federatedml/model/Scorecard.java

@@ -0,0 +1,98 @@
+/*
+ * Copyright 2019 The FATE Authors. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.webank.ai.fate.serving.federatedml.model;
+
+import com.webank.ai.fate.serving.common.model.MergeInferenceAware;
+import com.webank.ai.fate.serving.core.bean.Context;
+import com.webank.ai.fate.serving.core.bean.Dict;
+import com.webank.ai.fate.serving.core.constant.StatusCode;
+import com.webank.ai.fate.serving.core.exceptions.GuestMergeException;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+public class Scorecard extends BaseComponent implements Returnable, MergeInferenceAware{
+
+    private static final Logger logger = LoggerFactory.getLogger(Scorecard.class);
+    private static final double FLOAT_ZERO = 1e-8;
+
+    @Override
+    public int initModel(byte[] protoMeta, byte[] protoParam) {
+        return 0;
+    }
+
+    @Override
+    public Object getParam() {
+        return null;
+    }
+
+    @Override
+    public Map<String, Object> localInference(Context context, List<Map<String, Object>> input
+    ) {
+        // do nothing, calc in merge
+        return new HashMap<>(0);
+    }
+
+    @Override
+    public Map<String, Object> mergeRemoteInference(Context context, List<Map<String, Object>> localData, Map<String, Object> remoteData) {
+        logger.error("score card merge input local {}, remote {}", localData, remoteData);
+        Map<String, Object> data = localData.get(0);
+        Map<String, Object> result = this.handleRemoteReturnData(remoteData);
+        double localScore = 0;
+        if ((int) result.get(Dict.RET_CODE) == StatusCode.SUCCESS) {
+            if (data.get(Dict.SCORE) != null) {
+                localScore = ((Number) data.get(Dict.SCORE)).doubleValue();
+            } else {
+                throw new GuestMergeException("local result is invalid ");
+            }
+            result.put(Dict.SCORE, this.scorecardCalc(localScore));
+        }
+        return result;
+    }
+
+    private double scorecardCalc(double score) {
+        int upper_limit_ratio = 3;
+        int offset = 500;
+        int upper_limit_value = upper_limit_ratio * offset;
+        int lower_limit_value = 0;
+
+        double credit_score;
+        if(Math.abs(score - 0) <= FLOAT_ZERO && score >= 0){
+            credit_score = upper_limit_value;
+        }else if(Math.abs(score - 1) <= FLOAT_ZERO && score > 0){
+            credit_score = lower_limit_value;
+        }else if(score > 1 || score < 0){
+            credit_score = -1;
+        } else{
+            double odds = (double) ((1 - score) / score);
+            int factor = 20;
+            int factor_base = 2;
+            credit_score = offset + factor / Math.log(factor_base) * Math.log(odds);
+        }
+        if (credit_score > upper_limit_value) {
+            credit_score = upper_limit_value;
+        }
+        if(credit_score < lower_limit_value){
+            credit_score = lower_limit_value;
+        }
+        credit_score = Math.round(credit_score * 100.0) / 100.0;
+        return credit_score;
+    }
+}