Spark 3.5.5 ScalaDoc - org.apache.spark.mllib.linalg.DenseMatrix (original) (raw)
class DenseMatrix extends Matrix
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DenseMatrix
Matrix
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Instance Constructors
- new DenseMatrix(numRows: Int, numCols: Int, values: Array[Double])
- new DenseMatrix(numRows: Int, numCols: Int, values: Array[Double], isTransposed: Boolean)
Value Members
- final def !=(arg0: Any): Boolean
- final def ##(): Int
- final def ==(arg0: Any): Boolean
- def apply(i: Int, j: Int): Double
- final def asInstanceOf[T0]: T0
- def asML: ml.linalg.DenseMatrix
- def clone(): AnyRef
- def colIter: Iterator[Vector]
- def copy: DenseMatrix
- final def eq(arg0: AnyRef): Boolean
- def equals(o: Any): Boolean
- def finalize(): Unit
- final def getClass(): Class[_]
- def hashCode(): Int
- final def isInstanceOf[T0]: Boolean
- val isTransposed: Boolean
- def multiply(y: Vector): DenseVector
- def multiply(y: DenseVector): DenseVector
- def multiply(y: DenseMatrix): DenseMatrix
- final def ne(arg0: AnyRef): Boolean
- final def notify(): Unit
- final def notifyAll(): Unit
- def numActives: Int
- val numCols: Int
- def numNonzeros: Int
- val numRows: Int
- def rowIter: Iterator[Vector]
- final def synchronized[T0](arg0: ⇒ T0): T0
- def toArray: Array[Double]
- def toSparse: SparseMatrix
- def toString(maxLines: Int, maxLineWidth: Int): String
- def toString(): String
- def transpose: DenseMatrix
- val values: Array[Double]
- final def wait(): Unit
- final def wait(arg0: Long, arg1: Int): Unit
- final def wait(arg0: Long): Unit