com.datumbox.framework.core.machinelearning.regression

Class NLMS

java.lang.Object

com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer<MP,TP>

com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractModeler<MP,TP>

com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractRegressor<NLMS.ModelParameters,NLMS.TrainingParameters>

com.datumbox.framework.core.machinelearning.regression.NLMS

All Implemented Interfaces:

Savable, Parallelizable, PredictParallelizable, Trainable<NLMS.ModelParameters,NLMS.TrainingParameters>, TrainParallelizable, java.lang.AutoCloseable

public class NLMS
extends AbstractRegressor<NLMS.ModelParameters,NLMS.TrainingParameters>
implements PredictParallelizable, TrainParallelizable

Linear Regression model which uses the Normalised Least Mean Squares Algorithm. This implementation should be preferred from MatrixLinearRegression when the data can't fit the memory. References: http://cs229.stanford.edu/notes/cs229-notes1.pdf http://www.holehouse.org/mlclass/04_Linear_Regression_with_multiple_variables.html https://class.coursera.org/ml-003/lecture/index http://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-ridge-lasso-regression-python/

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NLMS.ModelParameters Base class for every ModelParameter class in the framework.
static class	NLMS.TrainingParameters The AbstractTrainingParameters class stores the parameters that can be changed before training the algorithm.

Nested classes/interfaces inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer

AbstractTrainer.AbstractModelParameters, AbstractTrainer.AbstractTrainingParameters

Nested classes/interfaces inherited from interface com.datumbox.framework.core.machinelearning.common.interfaces.PredictParallelizable

PredictParallelizable.Prediction

Method Summary

Modifier and Type	Method and Description
PredictParallelizable.Prediction	_predictRecord(Record r) Takes a single record, makes a prediction using the model and returns the result wrapped in the Prediction tuple.
boolean	isParallelized() Getter for the parallelized parameter.
void	setParallelized(boolean parallelized) Setter for the parallelized parameter.

Methods inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.modelers.AbstractModeler

predict

Methods inherited from class com.datumbox.framework.core.machinelearning.common.abstracts.AbstractTrainer

close, delete, fit, getModelParameters, getTrainingParameters, save

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface com.datumbox.framework.core.machinelearning.common.interfaces.PredictParallelizable

_predictDatasetParallel, _predictDatasetParallel

Method Detail

isParallelized

public boolean isParallelized()

Getter for the parallelized parameter.

Specified by:

isParallelized in interface Parallelizable

Returns:

setParallelized

public void setParallelized(boolean parallelized)

Setter for the parallelized parameter.

Specified by:

setParallelized in interface Parallelizable

_predictRecord

public PredictParallelizable.Prediction _predictRecord(Record r)

Takes a single record, makes a prediction using the model and returns the result wrapped in the Prediction tuple. The method assumes that the KnowledgeBase is be loaded.

Specified by:

_predictRecord in interface PredictParallelizable

Returns: