
SubmitX is an end-to-end development and production platform for machine learning. The platform is written in Java.
Beginners
For beginners, the best place to start is to use the SubmitX Visual Model Designer which comes with the “Autopilot” option. Beginners can upload a raw file, create new features,issue a learn request and instantly verify the predicted result.
Download the SubmitX Visual Model Designer from here, follow the installation instruction and instantly deploy your first machine-learning project.

Experts
Experts can extend the capability of the SubmitX ML Library by creating and plugging new algorithms, sub-classing existing algorithms, creating and extending feature engineering nodes.
public class JantricANNLearningEnv extends JantricLearningEnvBase
{
...
@Override
public HashMap<String, Double> learnFromData(ICJDataFrame dataFrame) throws JantricAttributeException
{
ICJMatrix _dataFrame = dataFrame.getDummyDataFrameMat(this.getDisEncod());
ICJHiddenLayerManager m_hdnLyrMgr = (ICJHiddenLayerManager) ( _actionNeuron).getGraphMemoryAccess(ICJHiddenLayerManager.NODE_TYPE);
m_hdnLyrMgr.setDataSize(_dataFrame.getNumRows());
m_hdnLyrMgr.setNumberOfFeatures(_numberOfFeatures);m_hdnLyrMgr.setActiv("SINUSOID");
ICJMatrix _outpt = m_hdnLyrMgr.getLearnedANNOutput(false); ICJMatrix _confusionMat = _testRegresand.getConfusionMatrix(_outpt);
double recall = _confusionMat.CJMatToCJBigMat().getAvgRecall().doubleValue();
double precision = _confusionMat.CJMatToCJBigMat().getAvgPrecision().doubleValue();
double f1Score = (2*precision*recall)/(recall+precision);