Modifier and Type | Interface and Description |
---|---|
interface |
AlgoOperator<T extends AlgoOperator<T>>
An AlgoOperator takes a list of tables as inputs and produces a list of tables as results.
|
interface |
Estimator<E extends Estimator<E,M>,M extends Model<M>>
Estimators are responsible for training and generating Models.
|
interface |
Model<T extends Model<T>>
A Model is typically generated by invoking
Estimator.fit(Table...) . |
interface |
Stage<T extends Stage<T>>
Base class for a node in a Pipeline or Graph.
|
interface |
Transformer<T extends Transformer<T>>
A Transformer is an AlgoOperator with the semantic difference that it encodes the Transformation
logic, such that a record in the output typically corresponds to one record in the input.
|
Modifier and Type | Class and Description |
---|---|
class |
Graph
A Graph acts as an Estimator.
|
class |
GraphModel
A GraphModel acts as a Model.
|
class |
Pipeline
A Pipeline acts as an Estimator.
|
class |
PipelineModel
A PipelineModel acts as a Model.
|
Modifier and Type | Interface and Description |
---|---|
interface |
KnnModelParams<T>
Params for
KnnModel . |
interface |
KnnParams<T>
Params for
Knn . |
Modifier and Type | Class and Description |
---|---|
class |
Knn
An Estimator which implements the KNN algorithm.
|
class |
KnnModel
A Model which classifies data using the model data computed by
Knn . |
Modifier and Type | Interface and Description |
---|---|
interface |
LogisticRegressionModelParams<T>
Params for
LogisticRegressionModel . |
interface |
LogisticRegressionParams<T>
Params for
LogisticRegression . |
Modifier and Type | Class and Description |
---|---|
class |
LogisticRegression
An Estimator which implements the logistic regression algorithm.
|
class |
LogisticRegressionModel
A Model which classifies data using the model data computed by
LogisticRegression . |
Modifier and Type | Interface and Description |
---|---|
interface |
NaiveBayesModelParams<T>
Params of
NaiveBayesModel . |
interface |
NaiveBayesParams<T>
Params of
NaiveBayes . |
Modifier and Type | Class and Description |
---|---|
class |
NaiveBayes
An Estimator which implements the naive bayes classification algorithm.
|
class |
NaiveBayesModel
A Model which classifies data using the model data computed by
NaiveBayes . |
Modifier and Type | Interface and Description |
---|---|
interface |
KMeansModelParams<T>
Params of
KMeansModel . |
interface |
KMeansParams<T>
Params of
KMeans . |
Modifier and Type | Class and Description |
---|---|
class |
KMeans
An Estimator which implements the k-means clustering algorithm.
|
class |
KMeansModel
A Model which clusters data into k clusters using the model data computed by
KMeans . |
Modifier and Type | Interface and Description |
---|---|
interface |
HasDistanceMeasure<T>
Interface for the shared distanceMeasure param.
|
interface |
HasFeaturesCol<T>
Interface for the shared featuresCol param.
|
interface |
HasGlobalBatchSize<T>
Interface for the shared global batch size param.
|
interface |
HasHandleInvalid<T>
Interface for the shared handleInvalid param.
|
interface |
HasInputCols<T>
Interface for the shared inputCols param.
|
interface |
HasLabelCol<T>
Interface for the shared label column param.
|
interface |
HasLearningRate<T>
Interface for the shared learning rate param.
|
interface |
HasMaxIter<T>
Interface for the shared maxIter param.
|
interface |
HasMultiClass<T>
Interface for the shared multi-class param.
|
interface |
HasOutputCols<T>
Interface for the shared outputCols param.
|
interface |
HasPredictionCol<T>
Interface for the shared prediction column param.
|
interface |
HasRawPredictionCol<T>
Interface for the shared raw prediction column param.
|
interface |
HasReg<T>
Interface for the shared regularization param.
|
interface |
HasSeed<T>
Interface for the shared seed param.
|
interface |
HasTol<T>
Interface for the shared tolerance param.
|
interface |
HasWeightCol<T>
Interface for the shared weight column param.
|
Modifier and Type | Interface and Description |
---|---|
interface |
OneHotEncoderParams<T>
Params of OneHotEncoderModel.
|
Modifier and Type | Class and Description |
---|---|
class |
OneHotEncoder
An Estimator which implements the one-hot encoding algorithm.
|
class |
OneHotEncoderModel
A Model which encodes data into one-hot format using the model data computed by
OneHotEncoder . |
Modifier and Type | Method and Description |
---|---|
static void |
ParamUtils.initializeMapWithDefaultValues(Map<Param<?>,Object> paramMap,
WithParams<?> instance)
Updates the paramMap with default values of all public final Param-typed fields of the given
instance.
|
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