gpalta.clustering
Class FitnessClustering
java.lang.Object
gpalta.clustering.FitnessClustering
- All Implemented Interfaces:
- Fitness
public class FitnessClustering
- extends java.lang.Object
- implements Fitness
Method Summary |
void |
calculate(Output outputs,
Individual ind,
TempOutputFactory tempOutputFactory,
DataHolder data)
Evaluates the tree in every sample, and then calculates its fitness
(and maybe some other stats, like hr0 and hr1 for classifiers),
recording them in the tree. |
Output |
getProcessedOutput(Output raw,
Individual ind,
TempOutputFactory tempOutputFactory,
DataHolder data)
|
void |
init(Config config,
DataHolder data,
Output desiredOutputs,
double[] weights)
Initializes the Fitness, receiving the desired outputs and
the wheights (importance) for each sample. |
void |
init(Config config,
DataHolder data,
java.lang.String fileName)
Initializes the Fitness, reading desired outputs from file |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
prototypes
public double[][] prototypes
classCenters
public double[] classCenters
FitnessClustering
public FitnessClustering()
init
public void init(Config config,
DataHolder data,
java.lang.String fileName)
- Description copied from interface:
Fitness
- Initializes the Fitness, reading desired outputs from file
- Specified by:
init
in interface Fitness
- Parameters:
config
- The evolution config, might be needed inside the Fitnessdata
- The current problem's data, might also be needed (for
instance to know the numer of samples used)fileName
- The file to read
init
public void init(Config config,
DataHolder data,
Output desiredOutputs,
double[] weights)
- Description copied from interface:
Fitness
- Initializes the Fitness, receiving the desired outputs and
the wheights (importance) for each sample.
- Specified by:
init
in interface Fitness
- Parameters:
config
- The evolution config, might be needed inside the Fitnessdata
- The current problem's data, might also be needed (for
instance to know the number of samples used)desiredOutputs
- The desired outputsweights
- The weight (importance) of each sample
calculate
public void calculate(Output outputs,
Individual ind,
TempOutputFactory tempOutputFactory,
DataHolder data)
- Description copied from interface:
Fitness
- Evaluates the tree in every sample, and then calculates its fitness
(and maybe some other stats, like hr0 and hr1 for classifiers),
recording them in the tree.
- Specified by:
calculate
in interface Fitness
getProcessedOutput
public Output getProcessedOutput(Output raw,
Individual ind,
TempOutputFactory tempOutputFactory,
DataHolder data)
- Specified by:
getProcessedOutput
in interface Fitness