case class MatrixVectorProduct(A: Matrix, x: Vector) extends Vector with Product with Serializable
Matrix vector multiplication (A * x)
- Alphabetic
- By Inheritance
- MatrixVectorProduct
- Serializable
- Product
- Equals
- Vector
- Tensor
- AnyRef
- Any
- by any2stringadd
- by StringFormat
- by Ensuring
- by ArrowAssoc
- Hide All
- Show All
- Public
- Protected
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- def *(y: Vector): Scalar
- Definition Classes
- Vector
- def *(y: Scalar): Vector
- Definition Classes
- Vector
- def *~(y: Vector): Matrix
- Definition Classes
- Vector
- def +(y: Vector): Vector
- Definition Classes
- Vector
- def -(y: Vector): Vector
- Definition Classes
- Vector
- def ->[B](y: B): (MatrixVectorProduct, B)
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toArrowAssoc[MatrixVectorProduct] performed by method ArrowAssoc in scala.Predef.
- Definition Classes
- ArrowAssoc
- Annotations
- @inline()
- def /(y: Scalar): Vector
- Definition Classes
- Vector
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- val A: Matrix
- def apply(env: Map[String, Tensor]): Vector
Applies the expression.
Applies the expression.
- Definition Classes
- MatrixVectorProduct → Vector
- def apply(env: (String, Tensor)*): Vector
Applies the expression.
Applies the expression.
- Definition Classes
- Vector
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def d(dx: VectorVar): Matrix
Returns the Jacobian matrix.
Returns the Jacobian matrix.
- Definition Classes
- MatrixVectorProduct → Vector
- def d(dx: Var): Vector
Returns the partial derivative.
Returns the partial derivative.
- Definition Classes
- MatrixVectorProduct → Vector
- def ensuring(cond: (MatrixVectorProduct) => Boolean, msg: => Any): MatrixVectorProduct
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toEnsuring[MatrixVectorProduct] performed by method Ensuring in scala.Predef.
- Definition Classes
- Ensuring
- def ensuring(cond: (MatrixVectorProduct) => Boolean): MatrixVectorProduct
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toEnsuring[MatrixVectorProduct] performed by method Ensuring in scala.Predef.
- Definition Classes
- Ensuring
- def ensuring(cond: Boolean, msg: => Any): MatrixVectorProduct
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toEnsuring[MatrixVectorProduct] performed by method Ensuring in scala.Predef.
- Definition Classes
- Ensuring
- def ensuring(cond: Boolean): MatrixVectorProduct
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toEnsuring[MatrixVectorProduct] performed by method Ensuring in scala.Predef.
- Definition Classes
- Ensuring
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def rank: Option[Int]
The rank of tensor, i.e.
- def shape: Option[Array[IntScalar]]
The shape of tensor, i.e the size of each dimension.
- def simplify: Vector
Simplify the expression.
Simplify the expression.
- Definition Classes
- MatrixVectorProduct → Vector
- def size: IntScalar
The size of vector.
The size of vector.
- Definition Classes
- MatrixVectorProduct → Vector
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- MatrixVectorProduct → AnyRef → Any
- def unary_+: Vector
- Definition Classes
- Vector
- def unary_-: Vector
- Definition Classes
- Vector
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- val x: Vector
Shadowed Implicit Value Members
- def +(other: String): String
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toany2stringadd[MatrixVectorProduct] performed by method any2stringadd in scala.Predef.
- Shadowing
- This implicitly inherited member is shadowed by one or more members in this class.
To access this member you can use a type ascription:(matrixVectorProduct: any2stringadd[MatrixVectorProduct]).+(other)
- Definition Classes
- any2stringadd
Deprecated Value Members
- def formatted(fmtstr: String): String
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toStringFormat[MatrixVectorProduct] performed by method StringFormat in scala.Predef.
- Definition Classes
- StringFormat
- Annotations
- @deprecated @inline()
- Deprecated
(Since version 2.12.16) Use
formatString.format(value)
instead ofvalue.formatted(formatString)
, or use thef""
string interpolator. In Java 15 and later,formatted
resolves to the new method in String which has reversed parameters.
- def →[B](y: B): (MatrixVectorProduct, B)
- Implicit
- This member is added by an implicit conversion from MatrixVectorProduct toArrowAssoc[MatrixVectorProduct] performed by method ArrowAssoc in scala.Predef.
- Definition Classes
- ArrowAssoc
- Annotations
- @deprecated
- Deprecated
(Since version 2.13.0) Use
->
instead. If you still wish to display it as one character, consider using a font with programming ligatures such as Fira Code.
Smile (Statistical Machine Intelligence and Learning Engine) is a fast and comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. With advanced data structures and algorithms, Smile delivers state-of-art performance.
Smile covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc.