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															@@ -1,5 +1,6 @@ 
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															 package com.tzld.piaoquan.ad.engine.service.predict.model.threshold; 
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															 package com.tzld.piaoquan.ad.engine.service.predict.model.threshold; 
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															+import com.alibaba.fastjson.JSONArray; 
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															 import com.alibaba.fastjson.JSONObject; 
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															 import com.alibaba.fastjson.JSONObject; 
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															 import com.tzld.piaoquan.ad.engine.commons.score.AdConfig; 
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															 import com.tzld.piaoquan.ad.engine.commons.score.AdConfig; 
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															 import com.tzld.piaoquan.ad.engine.commons.score.ScoreParam; 
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															 import com.tzld.piaoquan.ad.engine.commons.score.ScoreParam; 
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															@@ -74,7 +75,7 @@ public class ScoreV2ThresholdPredictModel extends ThresholdPredictModel { 
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															         List<AdRankItem> scoreResult = ScorerUtils 
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															         List<AdRankItem> scoreResult = ScorerUtils 
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															                 .getScorerPipeline(BREAK_CONFIG) 
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															                 .getScorerPipeline(BREAK_CONFIG) 
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															                 .scoring(scoreParam, userAdFeature, rankItems); 
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															                 .scoring(scoreParam, userAdFeature, rankItems); 
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															+        log.info("svc=predict modelName=modelV2 result={}", JSONArray.toJSONString(scoreResult)); 
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															         // 找出ctr*cvr最大的 
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															         // 找出ctr*cvr最大的 
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															         double max = -1; 
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															         double max = -1; 
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															         AdRankItem maxItem = null; 
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															         AdRankItem maxItem = null; 
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															@@ -100,7 +101,6 @@ public class ScoreV2ThresholdPredictModel extends ThresholdPredictModel { 
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															         result.put("threshold", threshold); 
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															         result.put("threshold", threshold); 
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															         result.put("score", maxItem == null ? -1 : maxItem.getScore()); 
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															         result.put("score", maxItem == null ? -1 : maxItem.getScore()); 
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															         result.put("ad_predict", adPredict); 
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															         result.put("ad_predict", adPredict); 
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															-        log.info("svc=predict modelName=modelV2 result={}", JSONObject.toJSONString(result)); 
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															         return result; 
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															         return result; 
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															     } 
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															     } 
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