eg

Class Iris

java.lang.Object

eg.Iris

public class Iris
extends java.lang.Object

Iris, a simple example of an application program that runs some MML-analysis of "Iris.csv". Includes Mixture-Models and a (decision-) classification-Tree. Also see [the book] and the [home page].

Field Summary

Fields

Modifier and Type	Field and Description
static Type.Tuple	R4 Type 'R4' is 4 CTS, i.e., R4, that is sepal and petal, length and width.
static Type.Tuple	R4Species Type 'R4Species' is a 5-tuple of dimensions and Species.
static Type.Enum	Species The Enum Type 'Species' is 'Iris-setosa | Iris-versicolor | Iris-virginica'.

Constructor Summary

Constructors

Constructor and Description
Iris()

Method Summary

Modifier and Type	Method and Description
static void	compare(java.lang.String caption, Estimator baseEst, Mixture.Est mxEst, Vector ds4, Vector ds5) Compare a no-mixture 'baseEst'-imated Model to a 'mxEst'-imated Mixture model on data-set 'ds4' (the full 'ds5' data-set is only for cross-tabulation).
static void	display(Model m, Vector ds) Print out a summary of Model 'm', its 1st and 2nd-part message lengths and its performance on data-set 'ds'.
static Model	exercise(java.lang.String caption, Estimator e, Vector ds) Using Estimator 'e', fit a Model to data-set 'ds' and show some results.
static Vector	getData(java.lang.String filename) Get the Iris data-set from the named file using Vector.csv(boolean, boolean, char, la.la.Type.Tuple, int, java.io.InputStream).
static void	main(java.lang.String[] argv) Run MML-analysis of the Iris data (Iris.csv), including a Mixture-Model and a (decision-) classification-Tree.
static java.lang.String	x2S(double x) Return just a few significant digits of x; uses Util.x2String(x).

Methods inherited from class java.lang.Object

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

Field Detail

Species

public static Type.Enum Species

The Enum Type 'Species' is 'Iris-setosa | Iris-versicolor | Iris-virginica'.

R4

public static Type.Tuple R4

Type 'R4' is 4 CTS, i.e., R⁴, that is sepal and petal, length and width.

R4Species

public static Type.Tuple R4Species

Type 'R4Species' is a 5-tuple of dimensions and Species.

Constructor Detail

Iris

public Iris()

Method Detail

x2S

public static java.lang.String x2S(double x)

Return just a few significant digits of x; uses Util.x2String(x).

getData

public static Vector getData(java.lang.String filename)

Get the Iris data-set from the named file using Vector.csv(boolean, boolean, char, la.la.Type.Tuple, int, java.io.InputStream). There are five columns (see variables) -- petal and sepal, length and width, and the Species.

exercise

public static Model exercise(java.lang.String caption,
                             Estimator e,
                             Vector ds)

Using Estimator 'e', fit a Model to data-set 'ds' and show some results.

display

public static void display(Model m,
                           Vector ds)

Print out a summary of Model 'm', its 1st and 2nd-part message lengths and its performance on data-set 'ds'.

compare

public static void compare(java.lang.String caption,
                           Estimator baseEst,
                           Mixture.Est mxEst,
                           Vector ds4,
                           Vector ds5)

Compare a no-mixture 'baseEst'-imated Model to a 'mxEst'-imated Mixture model on data-set 'ds4' (the full 'ds5' data-set is only for cross-tabulation).

main

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

Run MML-analysis of the Iris data (Iris.csv), including a Mixture-Model and a (decision-) classification-Tree.