Modifier and Type | Class and Description |
---|---|
class |
SVM
Implements a soft-margin SVM using the communication-efficient distributed dual coordinate
ascent algorithm (CoCoA) with hinge-loss function.
|
Modifier and Type | Class and Description |
---|---|
class |
KNN
Implements a
k -nearest neighbor join. |
Modifier and Type | Class and Description |
---|---|
class |
StochasticOutlierSelection
An implementation of the Stochastic Outlier Selection algorithm by Jeroen Jansen
|
Modifier and Type | Interface and Description |
---|---|
interface |
Predictor<Self>
Predictor trait for Flink's pipeline operators.
|
interface |
Transformer<Self extends Transformer<Self>>
Transformer trait for Flink's pipeline operators.
|
Modifier and Type | Class and Description |
---|---|
class |
ChainedPredictor<T extends Transformer<T>,P extends Predictor<P>>
|
class |
ChainedTransformer<L extends Transformer<L>,R extends Transformer<R>>
Transformer which represents the chaining of two Transformer . |
Modifier and Type | Method and Description |
---|---|
<Instance extends Estimator<Instance>,Model,Testing,PredictionValue> |
Predictor$.defaultEvaluateDataSetOperation(PredictOperation<Instance,Model,Testing,PredictionValue> predictOperation,
TypeInformation<Testing> testingTypeInformation,
TypeInformation<PredictionValue> predictionValueTypeInformation)
Default
EvaluateDataSetOperation which takes a PredictOperation to calculate a tuple
of true label value and predicted label value. |
<Instance extends Estimator<Instance>,Model,Testing,PredictionValue> |
Predictor$.defaultPredictDataSetOperation(PredictOperation<Instance,Model,Testing,PredictionValue> predictOperation,
TypeInformation<Testing> testingTypeInformation,
TypeInformation<PredictionValue> predictionValueTypeInformation)
Default
PredictDataSetOperation which takes a PredictOperation to calculate a tuple
of testing element and its prediction value. |
<Instance extends Estimator<Instance>,Model,Input,Output> |
Transformer$.defaultTransformDataSetOperation(TransformOperation<Instance,Model,Input,Output> transformOperation,
TypeInformation<Output> outputTypeInformation,
scala.reflect.ClassTag<Output> outputClassTag) |
Modifier and Type | Class and Description |
---|---|
class |
MinMaxScaler
Scales observations, so that all features are in a user-specified range.
|
class |
PolynomialFeatures
Maps a vector into the polynomial feature space.
|
class |
StandardScaler
Scales observations, so that all features have a user-specified mean and standard deviation.
|
Modifier and Type | Class and Description |
---|---|
class |
ALS
Alternating least squares algorithm to calculate a matrix factorization.
|
Modifier and Type | Class and Description |
---|---|
class |
MultipleLinearRegression
Multiple linear regression using the ordinary least squares (OLS) estimator.
|
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