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@ -84,7 +84,7 @@ Specify the learning task and the corresponding learning objective. The objectiv
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- "logloss": negative [log-likelihood](http://en.wikipedia.org/wiki/Log-likelihood)
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- "error": Binary classification error rate. It is calculated as #(wrong cases)/#(all cases). For the predictions, the evaluation will regard the instances with prediction value larger than 0.5 as positive instances, and the others as negative instances.
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- "merror": Multiclass classification error rate. It is calculated as #(wrong cases)/#(all cases).
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- "mlogloss": Multiclass logloss
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- "mlogloss": [Multiclass logloss](https://www.kaggle.com/wiki/MultiClassLogLoss)
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- "auc": [Area under the curve](http://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_curve) for ranking evaluation.
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- "ndcg":[Normalized Discounted Cumulative Gain](http://en.wikipedia.org/wiki/NDCG)
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- "map":[Mean average precision](http://en.wikipedia.org/wiki/Mean_average_precision#Mean_average_precision)
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