The following tests fail with windows and jdk 1.8 (I don't think this is windows or java related ;) ):

Failed tests: ElkanKMeansTest.testCluster_3args_2:106 expected:<3> but was:<4> RandomBallCoverTest.testSearch_Vec_double:114 jsat.linear.vectorcollection.RandomBallCover$RandomBallCoverFactory failed expected:<14> but was:<13> RandomBallCoverTest.testSearch_Vec_int:168 jsat.linear.vectorcollection.RandomBallCover$RandomBallCoverFactory failed 10 VPTreeMVTest.testSearch_Vec_int:171 jsat.linear.vectorcollection.VPTreeMV$VPTreeMVFactory failed 10 VPTreeTest.testSearch_Vec_double:113 jsat.linear.vectorcollection.VPTree$VPTreeFactory failed expected:<12> but was:<11> VPTreeTest.testSearch_Vec_int:167 jsat.linear.vectorcollection.VPTree$VPTreeFactory failed 1 FastMathTest.testPow:152 null

EDIT: It seems that some of the tests sometimes fail and sometimes pass. I did not have a closer look but maybe there are some random issues in the tests. This time I got the following result:

Failed tests: NewGLMNETTest.testSetC:109 null ElkanKMeansTest.testCluster_3args_2:106 expected:<3> but was:<4> NaiveKMeansTest.testCluster_3args_1:89 expected:<10> but was:<9> RandomBallCoverTest.testSearch_Vec_double:114 jsat.linear.vectorcollection.RandomBallCover$RandomBallCoverFactory failed expected:<14> but was:<7> RandomBallCoverTest.testSearch_Vec_int:168 jsat.linear.vectorcollection.RandomBallCover$RandomBallCoverFactory failed 20 VPTreeMVTest.testSearch_Vec_double:114 jsat.linear.vectorcollection.VPTreeMV$VPTreeMVFactory failed expected:<13> but was:<0> VPTreeMVTest.testSearch_Vec_int:171 jsat.linear.vectorcollection.VPTreeMV$VPTreeMVFactory failed 2 VPTreeTest.testSearch_Vec_double:113 jsat.linear.vectorcollection.VPTree$VPTreeFactory failed expected:<13> but was:<0> VPTreeTest.testSearch_Vec_int:167 jsat.linear.vectorcollection.VPTree$VPTreeFactory failed 1 Tests in error: PegasosKTest.testTrainC_ClassificationDataSet_ExecutorService:68 » FailedToFit DivisiveGlobalClustererTest.testCluster_DataSet_int_int_ExecutorService:129 » ArrayIndexOutOfBounds MiniBatchKMeansTest.testCluster_3args_1:94 » IndexOutOfBounds Index: 0, Size: ...

I ran the unit tests a few times in a row, and each time, a different set of 1 to 3 of them failed.

testTrainC_ClassificationDataSet(jsat.classifiers.trees.RandomForestTest) Time elapsed: 0.242 sec <<< FAILURE! testSearch_Vec_int(jsat.linear.vectorcollection.RandomBallCoverTest) Time elapsed: 0.013 sec <<< FAILURE!

Hi there,

I've just forked the project and wanted to make sure that it would compile. I've added a CI build with travis so that all the code is compiled and the tests also run.

I have this building on my fork but it would be better if you go to travis-ci.org and enable travis build for your repo to get the building working from the base. It will help with future pull requests to know there are no breaking changes

(Note: Once It's enabled, then just update the README to point to your own travis build instead of https://travis-ci.org/martingollogly/JSAT )

Thank you for sharing the great job you have done with the community.

While build works with Maven, I had a trouble compiling the code from Eclipse (Luna, Java 1.8). For methods loadSimple, loadClassification and loadRegression of class JSATData, compilation failed in the casts of load method response, e.g: return (SimpleDataSet) load(inRaw, true)); Compile error is: Cannot cast from DataSet<DataSet<DataSet>> to SimpleDataSet

Guess it's specific to my dev environment, so I'm not sending a pull request but just sharing a workaround with "double casting":

return (SimpleDataSet) ((DataSet<?>)load(inRaw, true));

Hi, I would like to save and load the result of the RandomForest training. When I used Java serialization and I got an Exception since getParam in the Parameter class creates Parameter Object that contains a Method field member (the getMethod variable is final and saved as part of the created Parameter object). The same happend when I used FST. I also tried to use Kryo but got an Exception since RandomDecisionTree does not have no-arg Constructor. I have millions of training data so I can't train it every time I want to use it, What should I do?

Thanks.

I had 3 test errors.

OS: Win 10

E:\data\finance\docs\ML\lib\JSAT-master\JSAT>java -version java version "1.7.0_79" Java(TM) SE Runtime Environment (build 1.7.0_79-b15) Java HotSpot(TM) 64-Bit Server VM (build 24.79-b02, mixed mode)

E:\data\finance\docs\ML\lib\JSAT-master\JSAT>javac -version javac 1.7.0_79

Results :

Failed tests: LinearBatchTest.testTrainWarmCMultieFast:175 Warm start wasn't faster? 30 vs 28 FastMathTest.testPow:152 null NadarayaWatsonTest.testTrainC_RegressionDataSet_ExecutorService:103 null

Tests run: 1049, Failures: 3, Errors: 0, Skipped: 0

[INFO] ------------------------------------------------------------------------ [INFO] BUILD FAILURE [INFO] ------------------------------------------------------------------------ [INFO] Total time: 03:28 min [INFO] Finished at: 2016-01-04T16:59:37-05:00 [INFO] Final Memory: 9M/244M [INFO] ------------------------------------------------------------------------ [ERROR] Failed to execute goal org.apache.maven.plugins:maven-surefire-plugin:2.18.1:test (default-test) on project JSAT: There are test failures. [ERROR] [ERROR] Please refer to E:\data\finance\docs\ML\lib\JSAT-master\JSAT\target\surefire-reports for the individual test results. [ERROR] -> [Help 1] org.apache.maven.lifecycle.LifecycleExecutionException: Failed to execute goal org.apache.maven.plugins:maven-surefire-plugin:2.18.1:test (default-test) on project JSAT: There are test failures.

Please refer to E:\data\finance\docs\ML\lib\JSAT-master\JSAT\target\surefire-reports for the individual test results. at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:212) at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:153) at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:145) at org.apache.maven.lifecycle.internal.LifecycleModuleBuilder.buildProject(LifecycleModuleBuilder.java:116) at org.apache.maven.lifecycle.internal.LifecycleModuleBuilder.buildProject(LifecycleModuleBuilder.java:80) at org.apache.maven.lifecycle.internal.builder.singlethreaded.SingleThreadedBuilder.build(SingleThreadedBuilder.java:51) at org.apache.maven.lifecycle.internal.LifecycleStarter.execute(LifecycleStarter.java:128) at org.apache.maven.DefaultMaven.doExecute(DefaultMaven.java:307) at org.apache.maven.DefaultMaven.doExecute(DefaultMaven.java:193) at org.apache.maven.DefaultMaven.execute(DefaultMaven.java:106) at org.apache.maven.cli.MavenCli.execute(MavenCli.java:862) at org.apache.maven.cli.MavenCli.doMain(MavenCli.java:286) at org.apache.maven.cli.MavenCli.main(MavenCli.java:197) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.codehaus.plexus.classworlds.launcher.Launcher.launchEnhanced(Launcher.java:289) at org.codehaus.plexus.classworlds.launcher.Launcher.launch(Launcher.java:229) at org.codehaus.plexus.classworlds.launcher.Launcher.mainWithExitCode(Launcher.java:415) at org.codehaus.plexus.classworlds.launcher.Launcher.main(Launcher.java:356) Caused by: org.apache.maven.plugin.MojoFailureException: There are test failures.

Please refer to E:\data\finance\docs\ML\lib\JSAT-master\JSAT\target\surefire-reports for the individual test results. at org.apache.maven.plugin.surefire.SurefireHelper.reportExecution(SurefireHelper.java:82) at org.apache.maven.plugin.surefire.SurefirePlugin.handleSummary(SurefirePlugin.java:254) at org.apache.maven.plugin.surefire.AbstractSurefireMojo.executeAfterPreconditionsChecked(AbstractSurefireMojo.java:854) at org.apache.maven.plugin.surefire.AbstractSurefireMojo.execute(AbstractSurefireMojo.java:722) at org.apache.maven.plugin.DefaultBuildPluginManager.executeMojo(DefaultBuildPluginManager.java:134) at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:208) ... 20 more

I tried to use PCA or MutualInfoFS to do dimensional reduction. After doing that I run the regression classifier, it crashes on the max dimension + 1.

MutualInfoFS transform = new MutualInfoFS(dataSet, 200);
dataSet.applyTransform(transform);
classifier = new StochasticMultinomialLogisticRegression(learningRate, iterations);
classifier.trainC(dataSet);

And the error is

Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 201 at jsat.linear.DenseVector.get(DenseVector.java:116) at jsat.linear.SparseVector.dot(SparseVector.java:511) at jsat.classifiers.linear.StochasticMultinomialLogisticRegression.classify(StochasticMultinomialLogisticRegression.java:539)

Is that a bug? Or did I miss something?

In order to facilitate the use of the library, is possible to have some interface like other library? You can look at "Apache Commons Math" where point are interface of Clusterable.

Here some reference: Clustering algorithms and distance measures Clusterable DBSCANClusterer

Very nice, that you set up a maven repository. Maybe, for those who are not familiar with maven, you could upload the jar to the releases tab. Could you also add src and doc jars to your maven repo? (with maven-source-plugin and maven-javadoc-plugin). What about adding JSAT to the central maven repository?! Then anyone could find JSAT without changing the pom file

Added equals and hashCode methods for almost all distributions to be able to check whether two distributions are equal and to be able to use them in HashSets/Maps.

• fixed javadoc errors/warnings, compile warnings *html in javadoc
  • unused java imports
  • missing serialVersionUID
• added SingleValueDistribution to DistributionSearch
• Changed every "new ArrayList<Double/Integer>" to new DoubleList/IntList

Sorry for this big pull request. Had to change something in almost every class.

In OrdinaryKriging.train(), when lup.det() is infinity that the LUPDecomposition will get a wrong X. However, I can get a right X when using singular value decomposition. So, I think it should be uesd SingularValueDecomposition instead of LUPDecomposition while lup.det() is infinity. Currently, just when lup.det() is NaN or very close to zero will use SingularValueDecomposition.

:eyes: Some source code analysis tools can help to find opportunities for improving software components. :thought_balloon: I propose to increase the usage of compound operators accordingly.

Would you like to integrate anything from a transformation result which can be generated by a command like the following? (:point_right: Please check also for questionable change suggestions because of an evolving search pattern.)

lokal$ perl -p -i.orig -0777 -e 's#\b(?<target>\S+)\s*=\s*\k<target>[ \t]*(?<operator>[+\-*/%^]|&(?!&)|\|(?!\|)|<<|>>>?)#$+{target} $+{operator}=#gm' $(find ~/Projekte/JSAT/lokal -name '*.java')

Maybe I'm missing something - but is it possible tu use MeanShift-Clustering with a given (fixed) bandwidth?

As far as I follow the implementation, even if I provide the KDE with a set bandwidth to the MeanShift-Constructor, it gets overwritten in MeanShift's cluster-method by calling mkde.setUsingData(dataSet, parallel);:

@Override
public int[] cluster(DataSet dataSet, boolean parallel, int[] designations)
{
    // ...
    
    final KernelFunction k = mkde.getKernelFunction();
    mkde.setUsingData(dataSet, parallel);
    mkde.scaleBandwidth(scaleBandwidthFactor);
        
    // ...
}

Scaling the bandwidth seems not sufficient for me, as the scaled bandwidth isn't fixed. But as this is done inside the cluster-step, there seems to be no way to intercept or re-set the bandwidth...

A simple example how I've tried to use MeanShift:

SimpleDataSet dataSet = ...
double sigma = ...
MetricKDE metricKDE = new MetricKDE(GaussKF.getInstance(), new EuclideanDistance());
metricKDE.setBandwith(sigma); // <-- gets ignored!
MeanShift meanShift = new MeanShift(metricKDE);
List<List<DataPoint>> clusters = meanShift.cluster(dataSet); // <-- cluster trigger's bandwidth-estimation

Actually, it's obvious, that the Kernel-Density-Estimation wants to estimate the bandwidth, but in my case, I need a consistent bandwidth for multiple runs and need 'only' the clustering-step for the data.

Any help appreciated - thank you.

Bumps junit from 4.10 to 4.13.1.

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

How to create maven project for JSAT? Could you tell me anyone the command and argument to create maven project for JSAT? I tried to add dependencies into POM.xml file, whatever is given but it didn't work. Please help me

Thanks and regards

I want to use LVQ with this library, but I don't know how to use it. I have data to train like this:

| Input | class target (prediction) | | ------ | ------ | | 1, 0, 0, 0, 1, 0 | 1 | | 0, 1, 1, 1, 1, 0 | 2 |

and the data to be tested like this:

| Input | class target (prediction) | | ------ | ------ | | 0, 1, 0, 0, 0, 1 | 1 | | 0, 0, 1, 1, 0, 0 | 2 |

how to implement LVQ using this library? Thank you in advance.