org.nd4j.linalg.api.rng.distribution.factory

## Interface DistributionFactory

• All Known Implementing Classes:
DefaultDistributionFactory

`public interface DistributionFactory`
Create a distribution
Author:
• ### Method Summary

All Methods
Modifier and Type Method and Description
`Distribution` ```createBinomial(int n, double p)```
Create a distribution
`Distribution` ```createBinomial(int n, INDArray p)```
Create a distribution
`Distribution` `createConstant(double value)`
Creates constant distribution
`Distribution` ```createLogNormal(double mean, double std)```
Creates a log-normal distribution
`Distribution` ```createNormal(double mean, double std)```
Create a normal distribution with the given mean and std
`Distribution` ```createNormal(INDArray mean, double std)```
Create a normal distribution with the given mean and std
`Distribution` `createOrthogonal(double gain)`
Creates orthogonal distribution
`Distribution` ```createTruncatedNormal(double mean, double std)```
Creates truncated normal distribution
`Distribution` ```createUniform(double min, double max)```
Create a uniform distribution with the given min and max
• ### Method Detail

• #### createBinomial

```Distribution createBinomial(int n,
INDArray p)```
Create a distribution
Parameters:
`n` - the number of trials
`p` - the probabilities
Returns:
the biniomial distribution with the given parameters
• #### createBinomial

```Distribution createBinomial(int n,
double p)```
Create a distribution
Parameters:
`n` - the number of trials
`p` - the probabilities
Returns:
the biniomial distribution with the given parameters
• #### createNormal

```Distribution createNormal(INDArray mean,
double std)```
Create a normal distribution with the given mean and std
Parameters:
`mean` - the mean
`std` - the standard deviation
Returns:
the distribution with the given mean and standard deviation
• #### createNormal

```Distribution createNormal(double mean,
double std)```
Create a normal distribution with the given mean and std
Parameters:
`mean` - the mean
`std` - the stnadard deviation
Returns:
the distribution with the given mean and standard deviation
• #### createUniform

```Distribution createUniform(double min,
double max)```
Create a uniform distribution with the given min and max
Parameters:
`min` - the min
`max` - the max
Returns:
the uniform distribution
• #### createLogNormal

```Distribution createLogNormal(double mean,
double std)```
Creates a log-normal distribution
Parameters:
`mean` -
`std` -
Returns:
• #### createTruncatedNormal

```Distribution createTruncatedNormal(double mean,
double std)```
Creates truncated normal distribution
Parameters:
`mean` -
`std` -
Returns:
• #### createOrthogonal

`Distribution createOrthogonal(double gain)`
Creates orthogonal distribution
Parameters:
`gain` -
Returns:
• #### createConstant

`Distribution createConstant(double value)`
Creates constant distribution
Parameters:
`value` -
Returns: