object PolyRegression extends ModelFactory
The PolyRegression
companion object provides factory functions and functions
for creating functional forms.
- Alphabetic
- By Inheritance
- PolyRegression
- ModelFactory
- Error
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def allForms(x: MatriD, ord: Int): MatriD
Create all forms/terms for each row/point placing them in a new matrix.
Create all forms/terms for each row/point placing them in a new matrix.
- x
the original un-expanded input/data matrix
- ord
the order (max degree) of the polynomial
- def allForms(x: MatriD): MatriD
Create all forms/terms for each row/point placing them in a new matrix.
Create all forms/terms for each row/point placing them in a new matrix.
- x
the original un-expanded input/data matrix
- Definition Classes
- ModelFactory
- def apply(x: MatriD, y: VectoD, ord: Int, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): PolyRegression
Create a
PolyRegression
object from a data matrix and a response vector.Create a
PolyRegression
object from a data matrix and a response vector. This factory function provides data rescaling.- x
the initial data/input matrix (before polynomial term expansion)
- y
the response/output m-vector
- ord
the order (k) of the polynomial (max degree)
- fname
the feature/variable names (use null for default)
- hparam
the hyper-parameters (use null for default)
- technique
the technique used to solve for b in x.t*x*b = x.t*y (use Cholesky for default)
- See also
ModelFactory
- def apply(t: VectoD, y: VectoD, ord: Int, fname: Strings, hparam: HyperParameter, technique: RegTechnique.RegTechnique): PolyRegression
Create a
PolyRegression
object from a combined data-response matrix.Create a
PolyRegression
object from a combined data-response matrix.- t
the initial data/input vector: t_i expands to x_i = [1, t_i, t_i2, ... t_ik]
- y
the response/ouput vector
- ord
the order (k) of the polynomial (max degree)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
- def apply(xy: MatriD, ord: Int, fname: Strings = null, hparam: HyperParameter = null, technique: RegTechnique.RegTechnique = Cholesky): PolyRegression
Create a
PolyRegression
object from a combined data-response matrix.Create a
PolyRegression
object from a combined data-response matrix.- xy
the initial combined data-response matrix (before polynomial term expansion)
- ord
the order (k) of the polynomial (max degree)
- hparam
the hyper-parameters
- technique
the technique used to solve for b in x.t*x*b = x.t*y
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- val drp: (Null, Null, RegTechnique.Value)
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- final def flaw(method: String, message: String): Unit
- Definition Classes
- Error
- def forms(v: VectoD, k: Int, nt: Int): VectoD
Given a 1-vector/point 'v', compute the values for all of its polynomial forms/terms, returning them as a vector.
Given a 1-vector/point 'v', compute the values for all of its polynomial forms/terms, returning them as a vector.
- v
the vector/point (i-th row of t) for creating forms/terms
- k
number of features/predictor variables (not counting intercept) = 1
- nt
the number of terms
- Definition Classes
- PolyRegression → ModelFactory
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- 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() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def numTerms(k: Int): Int
The number of terms/parameters in the model (assumes
Regression
with intercept.The number of terms/parameters in the model (assumes
Regression
with intercept. Override for expanded columns, e.g.,QuadRegression
.- k
the number of features/predictor variables (not counting intercept)
- Definition Classes
- ModelFactory
- val rescale: Boolean
The 'rescale' flag indicated whether the data is to be rescaled/normalized
The 'rescale' flag indicated whether the data is to be rescaled/normalized
- Attributes
- protected
- Definition Classes
- ModelFactory
- def rescaleOff(): Unit
Turn rescaling off.
Turn rescaling off.
- Definition Classes
- ModelFactory
- def rescaleOn(): Unit
Turn rescaling on.
Turn rescaling on.
- Definition Classes
- ModelFactory
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- 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()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated