DeepWalk.Builder (deeplearning4j-graph 1.0.0-M2.1 API)

java.lang.Object
- org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder<V,E>

Enclosing class:: DeepWalk<V,E>

public static class DeepWalk.Builder<V,E>
extends Object

Constructor Summary

Constructors
Constructor Description

Builder()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`DeepWalk<V,E>`	`build()`
`DeepWalk.Builder<V,E>`	`learningRate(double learningRate)`	Set the learning rate
`DeepWalk.Builder<V,E>`	`seed(long seed)`	Seed for random number generation (used for repeatability).
`DeepWalk.Builder<V,E>`	`vectorSize(int vectorSize)`	Sets the size of the vectors to be learned for each vertex in the graph
`DeepWalk.Builder<V,E>`	`windowSize(int windowSize)`	Sets the window size used in skipgram model

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Builder
```
public Builder()
```
- Method Detail
  - vectorSize
```
public DeepWalk.Builder<V,E> vectorSize(int vectorSize)
```
    Sets the size of the vectors to be learned for each vertex in the graph
  - learningRate
```
public DeepWalk.Builder<V,E> learningRate(double learningRate)
```
    Set the learning rate
  - windowSize
```
public DeepWalk.Builder<V,E> windowSize(int windowSize)
```
    Sets the window size used in skipgram model
  - seed
```
public DeepWalk.Builder<V,E> seed(long seed)
```
    Seed for random number generation (used for repeatability). Note however that parallel/async gradient descent might result in behaviour that is not repeatable, in spite of setting seed
  - build
```
public DeepWalk<V,E> build()
```