Creates settings for a Multilayer perceptron model
setMultiLayerPerceptron(
numLayers = c(1:8),
sizeHidden = c(2^(6:9)),
dropout = c(seq(0, 0.3, 0.05)),
sizeEmbedding = c(2^(6:9)),
estimatorSettings = setEstimator(learningRate = "auto", weightDecay = c(1e-06, 0.001),
batchSize = 1024, epochs = 30, device = "cpu"),
hyperParamSearch = "random",
randomSample = 100,
randomSampleSeed = NULL
)Arguments
- numLayers
Number of layers in network, default: 1:8
Amount of neurons in each default layer, default: 2^(6:9) (64 to 512)
- dropout
How much dropout to apply after first linear, default: seq(0, 0.3, 0.05)
- sizeEmbedding
Size of embedding default: 2^(6:9) (64 to 512)
- estimatorSettings
settings of Estimator created with `setEstimator`
- hyperParamSearch
Which kind of hyperparameter search to use random sampling or exhaustive grid search. default: 'random'
- randomSample
How many random samples from hyperparameter space to use
- randomSampleSeed
Random seed to sample hyperparameter combinations
Details
Model architecture