Package | Description |
---|---|
com.google.api.services.bigquery.model |
Modifier and Type | Method and Description |
---|---|
DoubleHparamSearchSpace |
DoubleHparamSearchSpace.clone() |
DoubleHparamSearchSpace |
HparamSearchSpaces.getColsampleBylevel()
Subsample ratio of columns for each level for boosted tree models.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getColsampleBynode()
Subsample ratio of columns for each node(split) for boosted tree models.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getColsampleBytree()
Subsample ratio of columns when constructing each tree for boosted tree models.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getDropout()
Dropout probability for dnn model training and boosted tree models using dart booster.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getL1Reg()
L1 regularization coefficient.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getL2Reg()
L2 regularization coefficient.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getLearnRate()
Learning rate of training jobs.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getMinSplitLoss()
Minimum split loss for boosted tree models.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getSubsample()
Subsample the training data to grow tree to prevent overfitting for boosted tree models.
|
DoubleHparamSearchSpace |
HparamSearchSpaces.getWalsAlpha()
Hyperparameter for matrix factoration when implicit feedback type is specified.
|
DoubleHparamSearchSpace |
DoubleHparamSearchSpace.set(String fieldName,
Object value) |
DoubleHparamSearchSpace |
DoubleHparamSearchSpace.setCandidates(DoubleCandidates candidates)
Candidates of the double hyperparameter.
|
DoubleHparamSearchSpace |
DoubleHparamSearchSpace.setRange(DoubleRange range)
Range of the double hyperparameter.
|
Modifier and Type | Method and Description |
---|---|
HparamSearchSpaces |
HparamSearchSpaces.setColsampleBylevel(DoubleHparamSearchSpace colsampleBylevel)
Subsample ratio of columns for each level for boosted tree models.
|
HparamSearchSpaces |
HparamSearchSpaces.setColsampleBynode(DoubleHparamSearchSpace colsampleBynode)
Subsample ratio of columns for each node(split) for boosted tree models.
|
HparamSearchSpaces |
HparamSearchSpaces.setColsampleBytree(DoubleHparamSearchSpace colsampleBytree)
Subsample ratio of columns when constructing each tree for boosted tree models.
|
HparamSearchSpaces |
HparamSearchSpaces.setDropout(DoubleHparamSearchSpace dropout)
Dropout probability for dnn model training and boosted tree models using dart booster.
|
HparamSearchSpaces |
HparamSearchSpaces.setL1Reg(DoubleHparamSearchSpace l1Reg)
L1 regularization coefficient.
|
HparamSearchSpaces |
HparamSearchSpaces.setL2Reg(DoubleHparamSearchSpace l2Reg)
L2 regularization coefficient.
|
HparamSearchSpaces |
HparamSearchSpaces.setLearnRate(DoubleHparamSearchSpace learnRate)
Learning rate of training jobs.
|
HparamSearchSpaces |
HparamSearchSpaces.setMinSplitLoss(DoubleHparamSearchSpace minSplitLoss)
Minimum split loss for boosted tree models.
|
HparamSearchSpaces |
HparamSearchSpaces.setSubsample(DoubleHparamSearchSpace subsample)
Subsample the training data to grow tree to prevent overfitting for boosted tree models.
|
HparamSearchSpaces |
HparamSearchSpaces.setWalsAlpha(DoubleHparamSearchSpace walsAlpha)
Hyperparameter for matrix factoration when implicit feedback type is specified.
|
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