mml

Class Tree

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.UPFunctionModel

mml.Tree

All Implemented Interfaces:

java.lang.Comparable<Value>

public class Tree
extends UPFunctionModel

The class of UnParameterised (Decision | Classification | Regression)- Tree FunctionModels. Its problem defining parameter is (iType, leafUPM) - which is quite general. The estimator is Tree.Est. The fully parameterised FunctionModels are Tree.M (abstract), Tree.Fork (abstract), Tree.Leaf, Tree.DFork and Tree.OFork.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	Tree.DFork A fully parameterised Tree FunctionModel that tests a Discrete Bounded column (variable) of the input datum to select a sub-Model into which to descend.
class	Tree.Est The class of Estimators for a Tree FunctionModel.
class	Tree.Fork Superclass of fully parameterised non-Leaf FunctionModels; see Tree.DFork and Tree.OFork.
class	Tree.Leaf A fully parameterised Tree FunctionModel consisting of a single Leaf; it contains a Model over the output (dependent) datum, 'od'.
class	Tree.M The superclass of fully parameterised (Decision | Classification | Regression) -Trees; see Tree.Leaf, Tree.DFork and Tree.OFork.
class	Tree.OFork A fully parameterised Tree FunctionModel that compares an ordered field (variable) of the input datum to the split to select a sub-Model into which to descend.
static class	Tree.Param The root class for the statistical parameter of a fully parameterised Tree FunctionModel.

Nested classes/interfaces inherited from class mml.UPFunctionModel

UPFunctionModel.K

Nested classes/interfaces inherited from class mml.UPModel

UPModel.Transform

Nested classes/interfaces inherited from class la.la.Function.Native

Function.Native.WithInverse

Nested classes/interfaces inherited from class la.la.Function

Function.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3

Nested classes/interfaces inherited from class la.la.Value

Value.Atomic, Value.Bool, Value.Char, Value.Chars, Value.Cts, Value.Defer, Value.Discrete, Value.Enum, Value.Inc_Or, Value.Int, Value.Lambda, Value.List, Value.Maybe, Value.Option, Value.Real, Value.Scannable, Value.Structured, Value.Triv, Value.Tuple

Field Summary

Fields

Modifier and Type	Field and Description
Type	iType The Type of the input datum (variable), id, in id→od.
UPModel	leafUPM The UnParameterised Model of the output datum, od, that is to be parameterised in each Leaf of the fully parameterised Tree.
static double	log2 loge(2), i.e., one bit.
static Type.Option	TreeParam The Type of the Tree.Param - statistical parameter - of a fully parameterised Tree.M FunctionModel.

Fields inherited from class mml.UPModel

dp

Fields inherited from class la.la.Value

C, comparator, CR, E, eight, ffalse, five, fiveR, four, fourR, half, negCR, negOne, negOneR, negTenR, nilVal, nine, None, one, oneR, PI, PIby2, point01, point1, point5, point9, quarter, seven, six, ten, tenR, three, threeR, triv, ttrue, two, twoR, zero, zeroR

Constructor Summary

Constructors

Constructor and Description
Tree(Value dp) Problem defining parameter dp is (iType, leafUPM).

Method Summary

Modifier and Type	Method and Description
Tree.Est	estimator(Value ps) Return an Estimator for a Tree FunctionModel, M:id→od.
static void	main(java.lang.String[] argv) main() allows Tree to be (slightly) tested, in isolation.
Tree.M	sp2Model(double msg1, double msg2, Value sp) Return a fully parameterised Tree FunctionModel.
Vector	stats(boolean add, Value ss0, Value ss1) Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false).
Vector	stats(Vector ds, int lo, int hi) Statistics ss = stats(ds), of data-set ds, is ds itself.

Methods inherited from class mml.UPFunctionModel

apply

Methods inherited from class mml.UPModel

defnParams, stats, stats, toString, transform

Methods inherited from class la.la.Function

bOp, fromBop, fromUop, type, uOp

Methods inherited from class la.la.Value

AoM, bOp, compareTo, cons, cts, elt, errMsg, error, force, isTuple, just, n, nElts, nlAoM, pair, print, quad, real, RTE, triple, tuple, UOE, x

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

log2

public static final double log2

log_e(2), i.e., one bit.

TreeParam

public static final Type.Option TreeParam

The Type of the Tree.Param - statistical parameter - of a fully parameterised Tree.M FunctionModel.

iType

public final Type iType

The Type of the input datum (variable), id, in id→od.

leafUPM

public final UPModel leafUPM

The UnParameterised Model of the output datum, od, that is to be parameterised in each Leaf of the fully parameterised Tree. In general the instances will have different statistical parameters. Note that leafUPM can be a simple UPModel -- Discretes, Continuous, Multivariate, etc. -- or even a UPFunctionModel (regression), say.

Constructor Detail

Tree

public Tree(Value dp)

Problem defining parameter dp is (iType, leafUPM). UPModel leafUPM is to be parameterised in each Leaf of a fully parameterised Tree.

Method Detail

sp2Model

public Tree.M sp2Model(double msg1,
                       double msg2,
                       Value sp)

Return a fully parameterised Tree FunctionModel.

Specified by:

sp2Model in class UPFunctionModel

stats

public Vector stats(Vector ds,
                    int lo,
                    int hi)

Statistics ss = stats(ds), of data-set ds, is ds itself.

Specified by:

stats in class UPModel

stats

public Vector stats(boolean add,
                    Value ss0,
                    Value ss1)

Description copied from class: UPModel

Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false). Also see stats(ds,lo,hi).

Specified by:

stats in class UPModel

estimator

public Tree.Est estimator(Value ps)

Return an Estimator for a Tree FunctionModel, M:id→od. Parameter ps is passed to leafUPM.estimator(ps).

Overrides:

estimator in class UPModel

main

public static void main(java.lang.String[] argv)

main() allows Tree to be (slightly) tested, in isolation.