Nonreproducible sequence of evaluations fixed (#2153)
As `num_round=2` there is no `0003.model` file after training.
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@ -97,15 +97,15 @@ lambda_bias = 0.01
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#### Get Predictions
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#### Get Predictions
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After training, we can use the output model to get the prediction of the test data:
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After training, we can use the output model to get the prediction of the test data:
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```
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```
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../../xgboost mushroom.conf task=pred model_in=0003.model
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../../xgboost mushroom.conf task=pred model_in=0002.model
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```
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```
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For binary classification, the output predictions are probability confidence scores in [0,1], corresponds to the probability of the label to be positive.
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For binary classification, the output predictions are probability confidence scores in [0,1], corresponds to the probability of the label to be positive.
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#### Dump Model
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#### Dump Model
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This is a preliminary feature, so far only tree model support text dump. XGBoost can display the tree models in text files and we can scan the model in an easy way:
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This is a preliminary feature, so far only tree model support text dump. XGBoost can display the tree models in text files and we can scan the model in an easy way:
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```
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```
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../../xgboost mushroom.conf task=dump model_in=0003.model name_dump=dump.raw.txt
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../../xgboost mushroom.conf task=dump model_in=0002.model name_dump=dump.raw.txt
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../../xgboost mushroom.conf task=dump model_in=0003.model fmap=featmap.txt name_dump=dump.nice.txt
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../../xgboost mushroom.conf task=dump model_in=0002.model fmap=featmap.txt name_dump=dump.nice.txt
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```
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```
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In this demo, the tree boosters obtained will be printed in dump.raw.txt and dump.nice.txt, and the latter one is easier to understand because of usage of feature mapping featmap.txt
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In this demo, the tree boosters obtained will be printed in dump.raw.txt and dump.nice.txt, and the latter one is easier to understand because of usage of feature mapping featmap.txt
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