apply google-java-style indentation and impose import orders....

This commit is contained in:
CodingCat
2016-03-03 09:32:23 -05:00
parent 0f367a6ade
commit e3dc67c6a0
17 changed files with 36 additions and 46 deletions

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@@ -19,10 +19,11 @@ import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import ml.dmlc.xgboost4j.*;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import ml.dmlc.xgboost4j.*;
/**
* an example user define objective and eval
* NOTE: when you do customized loss function, the default prediction value is margin

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@@ -1,15 +1,9 @@
package ml.dmlc.xgboost4j.demo;
import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import java.util.HashMap;
import ml.dmlc.xgboost4j.Rabit;
import ml.dmlc.xgboost4j.Booster;
import ml.dmlc.xgboost4j.DMatrix;
import ml.dmlc.xgboost4j.XGBoost;
import ml.dmlc.xgboost4j.XGBoostError;
import ml.dmlc.xgboost4j.*;
/**
* Distributed training example, used to quick test distributed training.

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@@ -15,14 +15,14 @@
*/
package ml.dmlc.xgboost4j.demo;
import java.util.HashMap;
import ml.dmlc.xgboost4j.Booster;
import ml.dmlc.xgboost4j.DMatrix;
import ml.dmlc.xgboost4j.XGBoost;
import ml.dmlc.xgboost4j.XGBoostError;
import ml.dmlc.xgboost4j.demo.util.CustomEval;
import java.util.HashMap;
/**
* this is an example of fit generalized linear model in xgboost
* basically, we are using linear model, instead of tree for our boosters

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@@ -17,6 +17,7 @@ package ml.dmlc.xgboost4j.demo.util;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import ml.dmlc.xgboost4j.DMatrix;
import ml.dmlc.xgboost4j.IEvaluation;
import ml.dmlc.xgboost4j.XGBoostError;

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@@ -15,12 +15,12 @@
*/
package ml.dmlc.xgboost4j.demo.util;
import org.apache.commons.lang3.ArrayUtils;
import java.io.*;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.lang3.ArrayUtils;
/**
* util class for loading data
*