17.1.3 Building a Customized DeepWalk Model
You can build a DeepWalk model using customized hyper-parameters as described in the following code:
opg4j> var model = analyst.deepWalkModelBuilder().
setMinWordFrequency(1).
setBatchSize(512).
setNumEpochs(1).
setLayerSize(100).
setLearningRate(0.05).
setMinLearningRate(0.0001).
setWindowSize(3).
setWalksPerVertex(6).
setWalkLength(4).
setSampleRate(0.00001).
setNegativeSample(2).
build()
DeepWalkModel model= analyst.deepWalkModelBuilder()
.setMinWordFrequency(1)
.setBatchSize(512)
.setNumEpochs(1)
.setLayerSize(100)
.setLearningRate(0.05)
.setMinLearningRate(0.0001)
.setWindowSize(3)
.setWalksPerVertex(6)
.setWalkLength(4)
.setSampleRate(0.00001)
.setNegativeSample(2)
.build();
model = analyst.deepwalk_builder(min_word_frequency=1,
batch_size=512,num_epochs=1,
layer_size=100,
learning_rate=0.05,
min_learning_rate=0.0001,
window_size=3,
walks_per_vertex=6,
walk_length=4,
sample_rate=0.00001,
negative_sample=2)
See DeepWalkModelBuilder in Javadoc for more explanation for each builder operation along with the default values.
Parent topic: Using the DeepWalk Algorithm