A B C D E G I K L M N O P Q R S T W
All Classes All Packages

A

accumulateGradients(double[]) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

accumulateTrainSize(long) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

add(MLData) - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

add(MLDataPair) - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

add(MLData, MLData) - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

B

BACK_PROPAGATION - Static variable in class ml.shifu.guagua.example.nn.NNConstants

beginLoad(int, int) - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

Setting input variable size and output target size.

C

calculateWeights(double[], double[]) - Method in class ml.shifu.guagua.example.nn.Weight

close() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

compute(MasterContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansMaster

Master computation by accumulating all the k center points sum values from all workers, then average to get new k center points.

compute(MasterContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNMaster

compute(MasterContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumMaster

D

DEFAULT_INITIAL_UPDATE - Static variable in class ml.shifu.guagua.example.nn.NNConstants

The starting update for a delta.

DELTA_MIN - Static variable in class ml.shifu.guagua.example.nn.NNConstants

The minimum delta value for a weight matrix value.

doCompute(MasterContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionMaster

doCompute(MasterContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionMaster

doCompute(WorkerContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorker

Using the new k centers to tag each record with index denoting the record belongs to which category.

doCompute(WorkerContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionWorker

doCompute(WorkerContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionWorker

doCompute(WorkerContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNWorker

doCompute(WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumSequenceFileWorker

doCompute(WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumWorker

doReadFields(DataInput) - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

doReadFields(DataInput) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

doReadFields(DataInput) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

doReadFields(DataInput) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

doReadFields(DataInput) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

doWrite(DataOutput) - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

doWrite(DataOutput) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

doWrite(DataOutput) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

doWrite(DataOutput) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

doWrite(DataOutput) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

E

endLoad() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

This method should be called once all the data has been loaded.

G

generateNetwork(int, int, int) - Static method in class ml.shifu.guagua.example.nn.NNUtils

Generate basic NN network object

getC() - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

getC() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

getCountList() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

getDiskCount() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getError() - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

getError() - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

getError() - Method in class ml.shifu.guagua.example.nn.Gradient

getErrorCalculation() - Method in class ml.shifu.guagua.example.nn.Gradient

getGradients() - Method in class ml.shifu.guagua.example.nn.Gradient

getGradients() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

getIdealSize() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getInputSize() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getK() - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

getK() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

getLayerDelta() - Method in class ml.shifu.guagua.example.nn.Gradient

getMemoryCount() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getNetwork() - Method in class ml.shifu.guagua.example.nn.Gradient

getParameters() - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

getParameters() - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

getPointList() - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

getPointList() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

getRecord() - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

getRecord(long, MLDataPair) - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getRecordCount() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

getTag() - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

getTestError() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

getTestingData() - Method in class ml.shifu.guagua.example.nn.NNWorker

getTrainError() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

getTrainingData() - Method in class ml.shifu.guagua.example.nn.NNWorker

getTrainSize() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

getWeights() - Method in class ml.shifu.guagua.example.nn.Gradient

getWeights() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

Gradient - Class in ml.shifu.guagua.example.nn

Gradient is copied from Encog framework.

Gradient(FlatNetwork, MLDataSet, double[], ErrorFunction) - Constructor for class ml.shifu.guagua.example.nn.Gradient

Construct a gradient worker.

GUAGUA_NN_ALGORITHM - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_ALGORITHM - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_HIDDEN_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_INPUT_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_LEARNING_RATE - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_OUTPUT_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_DEFAULT_THREAD_COUNT - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_HIDDEN_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_INPUT_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_LEARNING_RATE - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_OUTPUT - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_OUTPUT_NODES - Static variable in class ml.shifu.guagua.example.nn.NNConstants

GUAGUA_NN_THREAD_COUNT - Static variable in class ml.shifu.guagua.example.nn.NNConstants

I

init(MasterContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionMaster

init(MasterContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionMaster

init(WorkerContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorker

init(WorkerContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionWorker

init(WorkerContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionWorker

init(WorkerContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNWorker

init(WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumSequenceFileWorker

init(WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumWorker

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorker

Reading input line by line

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionWorker

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionWorker

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.nn.NNWorker

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.sum.SumSequenceFileWorker

initRecordReader(GuaguaFileSplit) - Method in class ml.shifu.guagua.example.sum.SumWorker

INVALID_TAG - Static variable in class ml.shifu.guagua.example.kmeans.TaggedRecord

isFirstIteration() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

isSupervised() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

iterator() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

K

KMEANS_CENTERS_OUTPUT - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMEANS_COLUMN_NUMBER - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMEANS_DATA_OUTPUT - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMEANS_DATA_SEPERATOR - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMEANS_K_CENTERS - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMEANS_K_NUMBER - Static variable in class ml.shifu.guagua.example.kmeans.KMeansContants

KMeansCentriodsOutput - Class in ml.shifu.guagua.example.kmeans

KMeansCentriodsOutput is used to write the final k centers to file system.

KMeansCentriodsOutput() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansCentriodsOutput

KMeansContants - Class in ml.shifu.guagua.example.kmeans

KMeansDataOutput - Class in ml.shifu.guagua.example.kmeans

KMeansDataOutput is used to save tagged data into HDFS.

KMeansDataOutput() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansDataOutput

KMeansMaster - Class in ml.shifu.guagua.example.kmeans

KMeansMaster computes new k center points for next iteration.

KMeansMaster() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansMaster

KMeansMasterParams - Class in ml.shifu.guagua.example.kmeans

KMeansMasterParams is the master results for KMeans distributed guagua application.

KMeansMasterParams() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansMasterParams

KMeansWorker - Class in ml.shifu.guagua.example.kmeans

KMeansWorker re-computes each record tagged with new category.

KMeansWorker() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansWorker

KMeansWorkerParams - Class in ml.shifu.guagua.example.kmeans

KMeansWorkerParams is the worker results for KMeans distributed guagua application.

KMeansWorkerParams() - Constructor for class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

L

LinearRegressionContants - Class in ml.shifu.guagua.example.lnr

LinearRegressionMaster - Class in ml.shifu.guagua.example.lnr

LinearRegressionMaster defines logic to update global linear regression model.

LinearRegressionMaster() - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionMaster

LinearRegressionOutput - Class in ml.shifu.guagua.example.lnr

LinearRegressionOutput is used to write the final model output to file system.

LinearRegressionOutput() - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionOutput

LinearRegressionParams - Class in ml.shifu.guagua.example.lnr

A model class to store linear regression weight on first iteration by using LinearRegressionParams.parameters, while in other iterations LinearRegressionParams.parameters is used to store gradients.

LinearRegressionParams() - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionParams

LinearRegressionParams(double[]) - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionParams

LinearRegressionParams(double[], double) - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionParams

LinearRegressionWorker - Class in ml.shifu.guagua.example.lnr

LinearRegressionWorker defines logic to accumulate local linear regression gradients.

LinearRegressionWorker() - Constructor for class ml.shifu.guagua.example.lnr.LinearRegressionWorker

load(GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<Text>, WorkerContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorker

Loading data into memory.

load(GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<Text>, WorkerContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionWorker

load(GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<Text>, WorkerContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionWorker

load(GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<Text>, WorkerContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNWorker

load(GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<Text>, WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumWorker

load(GuaguaWritableAdapter<Text>, GuaguaWritableAdapter<Text>, WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumSequenceFileWorker

LogisticRegressionContants - Class in ml.shifu.guagua.example.lr

LogisticRegressionMaster - Class in ml.shifu.guagua.example.lr

LogisticRegressionMaster defines logic to update global logistic regression model.

LogisticRegressionMaster() - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionMaster

LogisticRegressionOutput - Class in ml.shifu.guagua.example.lr

LogisticRegressionOutput is used to write the final model output to file system.

LogisticRegressionOutput() - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionOutput

LogisticRegressionParams - Class in ml.shifu.guagua.example.lr

A model class to store logistic regression weight on first iteration by using LogisticRegressionParams.parameters, while in other iterations LogisticRegressionParams.parameters is used to store gradients.

LogisticRegressionParams() - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionParams

LogisticRegressionParams(double[]) - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionParams

LogisticRegressionParams(double[], double) - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionParams

LogisticRegressionWorker - Class in ml.shifu.guagua.example.lr

LogisticRegressionWorker defines logic to accumulate local logistic regression gradients.

LogisticRegressionWorker() - Constructor for class ml.shifu.guagua.example.lr.LogisticRegressionWorker

LR_INPUT_DEFAULT_NUM - Static variable in class ml.shifu.guagua.example.lnr.LinearRegressionContants

LR_INPUT_DEFAULT_NUM - Static variable in class ml.shifu.guagua.example.lr.LogisticRegressionContants

LR_INPUT_NUM - Static variable in class ml.shifu.guagua.example.lnr.LinearRegressionContants

LR_INPUT_NUM - Static variable in class ml.shifu.guagua.example.lr.LogisticRegressionContants

LR_LEARNING_DEFAULT_RATE - Static variable in class ml.shifu.guagua.example.lnr.LinearRegressionContants

LR_LEARNING_DEFAULT_RATE - Static variable in class ml.shifu.guagua.example.lr.LogisticRegressionContants

LR_LEARNING_RATE - Static variable in class ml.shifu.guagua.example.lnr.LinearRegressionContants

LR_LEARNING_RATE - Static variable in class ml.shifu.guagua.example.lr.LogisticRegressionContants

M

main(String[]) - Static method in class ml.shifu.guagua.example.kmeans.TaggedRecord

main(String[]) - Static method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

MANHATTAN_PROPAGATION - Static variable in class ml.shifu.guagua.example.nn.NNConstants

MemoryDiskMLDataSet - Class in ml.shifu.guagua.example.nn

A hybrid data set combining BasicMLDataSet and BufferedMLDataSet together.

MemoryDiskMLDataSet(long, String) - Constructor for class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

Constructor with MemoryDiskMLDataSet.maxByteSize and MemoryDiskMLDataSet.fileName

MemoryDiskMLDataSet(long, String, int, int) - Constructor for class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

Constructor with MemoryDiskMLDataSet.maxByteSize, MemoryDiskMLDataSet.fileName, MemoryDiskMLDataSet.inputCount and MemoryDiskMLDataSet.outputCount.

MemoryDiskMLDataSet(String, int, int) - Constructor for class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

Constructor with MemoryDiskMLDataSet.fileName, MemoryDiskMLDataSet.inputCount and MemoryDiskMLDataSet.outputCount

ml.shifu.guagua.example.kmeans - package ml.shifu.guagua.example.kmeans

This package contains simple sum KMeans example code.

ml.shifu.guagua.example.lnr - package ml.shifu.guagua.example.lnr

Linear regression example by using batch gradient descent.

ml.shifu.guagua.example.lr - package ml.shifu.guagua.example.lr

Logistic regression example by using batch gradient descent.

ml.shifu.guagua.example.nn - package ml.shifu.guagua.example.nn

This package contains distributed neural network master and worker implementation.

ml.shifu.guagua.example.nn.meta - package ml.shifu.guagua.example.nn.meta

This package contains meta parameter object used in distributed neural network algorithm.

ml.shifu.guagua.example.sum - package ml.shifu.guagua.example.sum

This package contains simple sum example for all numbers in input.

N

NEGATIVE_ETA - Static variable in class ml.shifu.guagua.example.nn.NNConstants

The NEGATIVE ETA value.

NN_DEFAULT_COLUMN_SEPARATOR - Static variable in class ml.shifu.guagua.example.nn.NNConstants

NN_RECORD_SCALE - Static variable in class ml.shifu.guagua.example.nn.NNConstants

NN_TEST_SCALE - Static variable in class ml.shifu.guagua.example.nn.NNConstants

NNConstants - Class in ml.shifu.guagua.example.nn

Constants in guagua mapreduce.

NNMaster - Class in ml.shifu.guagua.example.nn

NNMaster is used to accumulate all workers NN parameters.

NNMaster() - Constructor for class ml.shifu.guagua.example.nn.NNMaster

NNOutput - Class in ml.shifu.guagua.example.nn

NNOutput is used to write the final model output to file system.

NNOutput() - Constructor for class ml.shifu.guagua.example.nn.NNOutput

NNParams - Class in ml.shifu.guagua.example.nn.meta

NNParams are used to save NN model info which can also be stored into ZooKeeper.

NNParams() - Constructor for class ml.shifu.guagua.example.nn.meta.NNParams

NNUtils - Class in ml.shifu.guagua.example.nn

Helper class for NN distributed training.

NNWorker - Class in ml.shifu.guagua.example.nn

NNWorker is used to compute NN model according to splits assigned.

NNWorker() - Constructor for class ml.shifu.guagua.example.nn.NNWorker

O

openAdditional() - Method in class ml.shifu.guagua.example.nn.MemoryDiskMLDataSet

P

POSITIVE_ETA - Static variable in class ml.shifu.guagua.example.nn.NNConstants

The POSITIVE ETA value.

postApplication(MasterContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansCentriodsOutput

postApplication(MasterContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionOutput

Get output file setting and write final sum value to HDFS file.

postApplication(MasterContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionOutput

Get output file setting and write final sum value to HDFS file.

postApplication(MasterContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNOutput

postApplication(MasterContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumOutput

Get output file setting and write final sum value to HDFS file.

postApplication(WorkerContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansDataOutput

postLoad(WorkerContext<KMeansMasterParams, KMeansWorkerParams>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorker

postLoad(WorkerContext<LinearRegressionParams, LinearRegressionParams>) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionWorker

postLoad(WorkerContext<LogisticRegressionParams, LogisticRegressionParams>) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionWorker

postLoad(WorkerContext<NNParams, NNParams>) - Method in class ml.shifu.guagua.example.nn.NNWorker

postLoad(WorkerContext<GuaguaWritableAdapter<LongWritable>, GuaguaWritableAdapter<LongWritable>>) - Method in class ml.shifu.guagua.example.sum.SumWorker

Q

QUICK_PROPAGATION - Static variable in class ml.shifu.guagua.example.nn.NNConstants

R

randomize(int, double[]) - Static method in class ml.shifu.guagua.example.nn.NNUtils

reset() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

RESILIENTPROPAGATION - Static variable in class ml.shifu.guagua.example.nn.NNConstants

run() - Method in class ml.shifu.guagua.example.nn.Gradient

Perform the gradient calculation

S

SCALEDCONJUGATEGRADIENT - Static variable in class ml.shifu.guagua.example.nn.NNConstants

setC(int) - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

setC(int) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

setCountList(List<Integer>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

setError(double) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

setError(double) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

setFirstIteration(boolean) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

setGradients(double[]) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

setK(int) - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

setK(int) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

setParameters(double[]) - Method in class ml.shifu.guagua.example.lnr.LinearRegressionParams

setParameters(double[]) - Method in class ml.shifu.guagua.example.lr.LogisticRegressionParams

setParams(BasicNetwork) - Method in class ml.shifu.guagua.example.nn.Gradient

setPointList(List<double[]>) - Method in class ml.shifu.guagua.example.kmeans.KMeansMasterParams

setPointList(List<double[]>) - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

setRecord(Double[]) - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

setTag(int) - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

setTestError(double) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

setTestingData(MLDataSet) - Method in class ml.shifu.guagua.example.nn.NNWorker

setTrainError(double) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

setTrainingData(MLDataSet) - Method in class ml.shifu.guagua.example.nn.NNWorker

setTrainSize(long) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

setWeights(double[]) - Method in class ml.shifu.guagua.example.nn.Gradient

setWeights(double[]) - Method in class ml.shifu.guagua.example.nn.meta.NNParams

sign(double) - Static method in class ml.shifu.guagua.example.nn.NNUtils

Determine the sign of the value.

SumMaster - Class in ml.shifu.guagua.example.sum

Sum all workers' results together.

SumMaster() - Constructor for class ml.shifu.guagua.example.sum.SumMaster

SumOutput - Class in ml.shifu.guagua.example.sum

SumOutput is used to write the final model output to file system.

SumOutput() - Constructor for class ml.shifu.guagua.example.sum.SumOutput

SumSequenceFileWorker - Class in ml.shifu.guagua.example.sum

SumSequenceFileWorker is used to accumulate the sum value for each line.

SumSequenceFileWorker() - Constructor for class ml.shifu.guagua.example.sum.SumSequenceFileWorker

SumWorker - Class in ml.shifu.guagua.example.sum

SumWorker is used to accumulate the sum value for each line.

SumWorker() - Constructor for class ml.shifu.guagua.example.sum.SumWorker

T

TaggedRecord - Class in ml.shifu.guagua.example.kmeans

Data records with tag.

TaggedRecord() - Constructor for class ml.shifu.guagua.example.kmeans.TaggedRecord

TaggedRecord(Double[]) - Constructor for class ml.shifu.guagua.example.kmeans.TaggedRecord

TaggedRecord(Double[], int) - Constructor for class ml.shifu.guagua.example.kmeans.TaggedRecord

toString() - Method in class ml.shifu.guagua.example.kmeans.KMeansWorkerParams

toString() - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

toString() - Method in class ml.shifu.guagua.example.nn.meta.NNParams

toString(String) - Method in class ml.shifu.guagua.example.kmeans.TaggedRecord

W

Weight - Class in ml.shifu.guagua.example.nn

Weight is used to update NN weights according to propagation option.

Weight(int, double, double, String) - Constructor for class ml.shifu.guagua.example.nn.Weight

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