Classify a record
Input:
data - training data in a table format where each row represents
an instance, and each column represents an attribute (feature).
This function selects the maximum-likelihood class label given a data instance
Input:
instance - feature vector (discrete finite feature values represented by integers)
selectedFeatures - boolean array specifying selected features (by default, null -all features included)
Clear the ruleset of all variables and rules, clear out the
trace logs, set the ruleset name to the empty string (""), and
set all ruleset options (alphacut, correlation method, and so on)
to default values.
The Fuzzy System (Fs) package defines a fuzzy rule language, a
fuzzy ruleset editor that you can use to create, test, and save
source fuzzy rules as well as ready-to-run serialized fuzzy agents
(the editor is integrated into the AbleEditor, but also can be run
as a stand-alone tool), a fuzzy inference engine, and objects and
APIs for creating and running fuzzy rulesets under program
control.
The EDITOR package provides a set of objects that implement a GUI development environment for constructing hybrid intelligent agents using AbleBeans and AbleAgents as components.
SimpleAbleAgent - How to create a custom AbleAgent
This example shows the easiest method for creating a custom AbleAgent
by extending the AbleDefaultAgent
base class.
SimpleAbleBean - How to create a custom AbleBean
This example shows the easiest method for creating a custom AbleBean,
by extending the AbleObject
base class.
There are three java parts that must be created for any
AbleBean:
The bean class file (SimpleAbleBean.java)
The bean info file (SimpleAbleBeanInfo.java)
The bean customizer file (SimpleAbleBeanCustomizer.java)
To see how the SimpleAbleBean works, go to the Samples
panel on the icon palette. Move the mouse slowly over
each icon and a tooltip text window will display the name of the
bean. Click on the icon for the "SimpleBean".
This will create an instance and place it on the canvas.
FIPA agents in this package include an AMS, an ACC, and a DF,
as well as a default FIPA agent that can be used as a base for
building FIPA-compliant agents.
Given a prospective chromosome
a) see if dups are allowed and if it is unique
b) if ok, create a child genetic object from the chromsome
and initialize the associated bean (if any)
given a newly derived chromosome(s), create a new population member(s)
and initialize it/them
Note: could be zero, one or two (depending on operators and if no dups allowed)
Generate replacementSize population members through application of genetic operators
Note: if replacementSize = populationSize we use elitism, the best member (highest fitness) is always carried over