Modifier and Type | Interface and Description |
---|---|
interface |
Estimator<E extends Estimator<E,M>,M extends Model<M>>
Estimators are responsible for training and generating Models.
|
Modifier and Type | Class and Description |
---|---|
class |
Graph
A Graph acts as an Estimator.
|
class |
Pipeline
A Pipeline acts as an Estimator.
|
Modifier and Type | Method and Description |
---|---|
Estimator<?,?> |
GraphBuilder.buildEstimator(TableId[] inputs,
TableId[] outputs)
Wraps nodes of the graph into an Estimator.
|
Estimator<?,?> |
GraphBuilder.buildEstimator(TableId[] inputs,
TableId[] outputs,
TableId[] inputModelData,
TableId[] outputModelData)
Wraps nodes of the graph into an Estimator.
|
Estimator<?,?> |
GraphBuilder.buildEstimator(TableId[] estimatorInputs,
TableId[] modelInputs,
TableId[] outputs,
TableId[] inputModelData,
TableId[] outputModelData)
Wraps nodes of the graph into an Estimator.
|
Modifier and Type | Method and Description |
---|---|
TableId[] |
GraphBuilder.addEstimator(Estimator<?,?> estimator,
TableId... inputs)
Adds an Estimator in the graph.
|
TableId[] |
GraphBuilder.addEstimator(Estimator<?,?> estimator,
TableId[] estimatorInputs,
TableId[] modelInputs)
Adds an Estimator in the graph.
|
TableId[] |
GraphBuilder.getModelDataFromEstimator(Estimator<?,?> estimator)
When the graph runs as Estimator, it first generates a GraphModel that contains the Model
fitted by the given Estimator.
|
void |
GraphBuilder.setModelDataOnEstimator(Estimator<?,?> estimator,
TableId... inputs)
When the graph runs as Estimator, it first generates a GraphModel that contains the Model
fitted by the given Estimator.
|
Modifier and Type | Class and Description |
---|---|
class |
Knn
An Estimator which implements the KNN algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
LinearSVC
An Estimator which implements the linear support vector classification.
|
Modifier and Type | Class and Description |
---|---|
class |
LogisticRegression
An Estimator which implements the logistic regression algorithm.
|
class |
OnlineLogisticRegression
An Estimator which implements the online logistic regression algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
NaiveBayes
An Estimator which implements the naive bayes classification algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
KMeans
An Estimator which implements the k-means clustering algorithm.
|
class |
OnlineKMeans
OnlineKMeans extends the function of
KMeans , supporting to train a K-Means model
continuously according to an unbounded stream of train data. |
Modifier and Type | Class and Description |
---|---|
class |
CountVectorizer
An Estimator which converts a collection of text documents to vectors of token counts.
|
Modifier and Type | Class and Description |
---|---|
class |
IDF
An Estimator that computes the inverse document frequency (IDF) for the input documents.
|
Modifier and Type | Class and Description |
---|---|
class |
Imputer
The imputer for completing missing values of the input columns.
|
Modifier and Type | Class and Description |
---|---|
class |
KBinsDiscretizer
An Estimator which implements discretization (also known as quantization or binning) to transform
continuous features into discrete ones.
|
Modifier and Type | Class and Description |
---|---|
class |
MinHashLSH
An Estimator that implements the MinHash LSH algorithm, which supports LSH for Jaccard distance.
|
Modifier and Type | Class and Description |
---|---|
class |
MaxAbsScaler
An Estimator which implements the MaxAbsScaler algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
MinMaxScaler
An Estimator which implements the MinMaxScaler algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
OneHotEncoder
An Estimator which implements the one-hot encoding algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
RobustScaler
An Estimator which scales features using statistics that are robust to outliers.
|
Modifier and Type | Class and Description |
---|---|
class |
OnlineStandardScaler
An Estimator which implements the online standard scaling algorithm, which is the online version
of
StandardScaler . |
class |
StandardScaler
An Estimator which implements the standard scaling algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
StringIndexer
An Estimator which implements the string indexing algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
UnivariateFeatureSelector
An Estimator which selects features based on univariate statistical tests against labels.
|
Modifier and Type | Class and Description |
---|---|
class |
VarianceThresholdSelector
An Estimator which implements the VarianceThresholdSelector algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
VectorIndexer
An Estimator which implements the vector indexing algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
LinearRegression
An Estimator which implements the linear regression algorithm.
|
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