public class LinearRegressionParams
extends ml.shifu.guagua.io.HaltBytable
parameters, while in other
iterations parameters is used to store gradients.
To make all workers started at the same model, master will compute a consistent model weights at the first iteration and then send to all the workers. Workers will start computing from the second iteration.
Workers are responsible to compute local accumulated gradients and send to master while master accumulates all gradients together to build a global model.
| Constructor and Description |
|---|
LinearRegressionParams() |
LinearRegressionParams(double[] parameters) |
LinearRegressionParams(double[] parameters,
double error) |
| Modifier and Type | Method and Description |
|---|---|
void |
doReadFields(DataInput in) |
void |
doWrite(DataOutput out) |
double |
getError() |
double[] |
getParameters() |
void |
setError(double error) |
void |
setParameters(double[] parameters) |
public LinearRegressionParams()
public LinearRegressionParams(double[] parameters)
public LinearRegressionParams(double[] parameters,
double error)
public double[] getParameters()
public void setParameters(double[] parameters)
public double getError()
public void setError(double error)
public void doWrite(DataOutput out) throws IOException
doWrite in class ml.shifu.guagua.io.HaltBytableIOExceptionpublic void doReadFields(DataInput in) throws IOException
doReadFields in class ml.shifu.guagua.io.HaltBytableIOExceptionCopyright © 2015. All Rights Reserved.