Uses of Class
org.apache.flink.ml.linalg.DenseVector

Packages that use DenseVector

Package	Description
org.apache.flink.ml.classification.knn
org.apache.flink.ml.classification.logisticregression
org.apache.flink.ml.classification.naivebayes
org.apache.flink.ml.clustering.kmeans
org.apache.flink.ml.common.feature
org.apache.flink.ml.linalg
org.apache.flink.ml.linalg.typeinfo

Uses of DenseVector in org.apache.flink.ml.classification.knn

Fields in org.apache.flink.ml.classification.knn declared as DenseVector

Modifier and Type	Field and Description
DenseVector	KnnModelData.featureNormSquares
DenseVector	KnnModelData.labels

Constructors in org.apache.flink.ml.classification.knn with parameters of type DenseVector

Constructor and Description
KnnModelData(DenseMatrix packedFeatures, DenseVector featureNormSquares, DenseVector labels)

Uses of DenseVector in org.apache.flink.ml.classification.logisticregression

Fields in org.apache.flink.ml.classification.logisticregression declared as DenseVector

Modifier and Type	Field and Description
DenseVector	LogisticRegressionModelData.coefficient

Methods in org.apache.flink.ml.classification.logisticregression with parameters of type DenseVector

Modifier and Type	Method and Description
void	LogisticGradient.computeGradient(List<LabeledPointWithWeight> dataPoints, DenseVector coefficient, DenseVector cumGradient) Computes gradient on a set of samples.
org.apache.flink.api.java.tuple.Tuple2<Double,Double>	LogisticGradient.computeLoss(List<LabeledPointWithWeight> dataPoints, DenseVector coefficient) Computes weight sum and loss sum on a set of samples.

Constructors in org.apache.flink.ml.classification.logisticregression with parameters of type DenseVector

Constructor and Description
LogisticRegressionModelData(DenseVector coefficient)

Uses of DenseVector in org.apache.flink.ml.classification.naivebayes

Fields in org.apache.flink.ml.classification.naivebayes declared as DenseVector

Modifier and Type	Field and Description
DenseVector	NaiveBayesModelData.labels Value of labels.
DenseVector	NaiveBayesModelData.piArray Log of class priors, whose dimension is C (number of classes).

Constructors in org.apache.flink.ml.classification.naivebayes with parameters of type DenseVector

Constructor and Description
NaiveBayesModelData(Map<Double,Double>[][] theta, DenseVector piArray, DenseVector labels)

Uses of DenseVector in org.apache.flink.ml.clustering.kmeans

Fields in org.apache.flink.ml.clustering.kmeans declared as DenseVector

Modifier and Type	Field and Description
DenseVector[]	KMeansModelData.centroids

Method parameters in org.apache.flink.ml.clustering.kmeans with type arguments of type DenseVector

Modifier and Type	Method and Description
static org.apache.flink.streaming.api.datastream.DataStream<DenseVector[]>	KMeans.selectRandomCentroids(org.apache.flink.streaming.api.datastream.DataStream<DenseVector> data, int k, long seed)

Constructors in org.apache.flink.ml.clustering.kmeans with parameters of type DenseVector

Constructor and Description
KMeansModelData(DenseVector[] centroids)

Uses of DenseVector in org.apache.flink.ml.common.feature

Methods in org.apache.flink.ml.common.feature that return DenseVector

Modifier and Type	Method and Description
DenseVector	LabeledPointWithWeight.getFeatures()

Methods in org.apache.flink.ml.common.feature with parameters of type DenseVector

Modifier and Type	Method and Description
void	LabeledPointWithWeight.setFeatures(DenseVector features)

Constructors in org.apache.flink.ml.common.feature with parameters of type DenseVector

Constructor and Description
LabeledPointWithWeight(DenseVector features, double label, double weight)

Uses of DenseVector in org.apache.flink.ml.linalg

Methods in org.apache.flink.ml.linalg that return DenseVector

Modifier and Type	Method and Description
static DenseVector	Vectors.dense(double... values) Creates a dense vector from its values.

Methods in org.apache.flink.ml.linalg with parameters of type DenseVector

Modifier and Type	Method and Description
static double	BLAS.asum(DenseVector x) \sum_i |x_i| .
static void	BLAS.axpy(double a, DenseVector x, DenseVector y) y += a * x .
static double	BLAS.dot(DenseVector x, DenseVector y) x \cdot y .
static void	BLAS.gemv(double alpha, DenseMatrix matrix, boolean transMatrix, DenseVector x, double beta, DenseVector y) y = alpha * matrix * x + beta * y or y = alpha * (matrix^T) * x + beta * y.
static double	BLAS.norm2(DenseVector x) \sqrt(\sum_i x_i * x_i) .
static void	BLAS.scal(double a, DenseVector x) x = x * a .

Uses of DenseVector in org.apache.flink.ml.linalg.typeinfo

Methods in org.apache.flink.ml.linalg.typeinfo that return DenseVector

Modifier and Type	Method and Description
DenseVector	DenseVectorSerializer.copy(DenseVector from)
DenseVector	DenseVectorSerializer.copy(DenseVector from, DenseVector reuse)
DenseVector	DenseVectorSerializer.createInstance()
DenseVector	DenseVectorSerializer.deserialize(org.apache.flink.core.memory.DataInputView source)
DenseVector	DenseVectorSerializer.deserialize(DenseVector reuse, org.apache.flink.core.memory.DataInputView source)

Methods in org.apache.flink.ml.linalg.typeinfo that return types with arguments of type DenseVector

Modifier and Type	Method and Description
org.apache.flink.api.common.typeutils.TypeSerializer<DenseVector>	DenseVectorTypeInfo.createSerializer(org.apache.flink.api.common.ExecutionConfig executionConfig)
org.apache.flink.api.common.typeinfo.TypeInformation<DenseVector>	DenseVectorTypeInfoFactory.createTypeInfo(Type t, Map<String,org.apache.flink.api.common.typeinfo.TypeInformation<?>> genericParameters)
Class<DenseVector>	DenseVectorTypeInfo.getTypeClass()
org.apache.flink.api.common.typeutils.TypeSerializerSnapshot<DenseVector>	DenseVectorSerializer.snapshotConfiguration()

Methods in org.apache.flink.ml.linalg.typeinfo with parameters of type DenseVector

Modifier and Type	Method and Description
DenseVector	DenseVectorSerializer.copy(DenseVector from)
DenseVector	DenseVectorSerializer.copy(DenseVector from, DenseVector reuse)
DenseVector	DenseVectorSerializer.deserialize(DenseVector reuse, org.apache.flink.core.memory.DataInputView source)
void	DenseVectorSerializer.serialize(DenseVector vector, org.apache.flink.core.memory.DataOutputView target)