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 |
GradientDescent
Base class which performs Stochastic Gradient Descent optimization using mini batches.
|
class |
GradientDescentL1
Implementation of a SGD solver with L1 regularization.
|
class |
GradientDescentL2
Implementation of a SGD solver with L2 regularization.
|
class |
IterativeSolver
An abstract class for iterative optimization algorithms
|
class |
SimpleGradientDescent
Implementation of a SGD solver without regularization.
|
class |
Solver
Base class for optimization algorithms
|
Modifier and Type | Interface and Description |
---|---|
interface |
Estimator<Self>
Base trait for Flink's pipeline operators.
|
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 | 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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