Home

APS
Downloads
Buy APS

Support
Register
Contact us

Knowledge Base of APS

Subscribe to the GEPList
 
Visit GEP

 

APS Editions

Panels
 
The Panels Menu gives access to the following sub-menus:

Report
Shows the report of the active run.

Training Data 
Shows and plots the training data.

Testing Data 
Shows and plots the testing data.

Transformed TS 
Shows and plots the time series after its transformation for training.

Original TS 
Shows and plots the original time series.

General Settings
Gives access to all the general settings of a run, such as number of chromosomes, number of genes, linking function, etc.

Fitness Function
Gives access to the Fitness Function Window where the fitness function is chosen and/or designed.

Genetic Operators
Gives access to the Genetic Operators Window where the degree of genetic modification is chosen.

Numerical Constants
Gives access to the Numerical Constants Window where the parameters necessary for handling random numerical constants are chosen.

Functions (Math)
Gives access to all the functions and rules, including Dynamic UDFs (DDFs).

Static UDFs
Gives access to all the static UDFs.

Run
Shows the Run Panel.

History
Shows the evolutionary history of the run.

Training Results
Compares the target values with the predicted values using either a Table or Charts for the training set. Shows also essential statistical indexes of performance on the training set.

Testing Results
Compares the target values with the predicted values using either a Table or Charts for the testing set. Shows also essential statistical indexes used for evaluating the generalizing capabilities on the testing set.

Predictions (Time Series)
Shows and plots the output of the model on the recursive predictions.

Recursive Testing (Time Series)
Compares the target values with the output of the model on the recursive testing using Tables and Charts. Shows also essential statistical indexes of the predictive performance on the recursive testing.

Training (Time Series)
Compares the target values with the predicted values using Tables and Charts on the training set. Shows also essential statistical indexes of performance on the training set.

Expression Tree
Shows the Expression Tree representation of the model.

Model in Karva
Shows the model in Karva notation.

Model in C#
Shows the model in C#.

Model in C++
Shows the model in C++.

Model in C
Shows the model in C.

Model in Fortran
Shows the model in Fortran.

Model in Java
Shows the model in Java.

Model in Javascript
Shows the model in JavaScript.

Model in VB.NET
Shows the model in VB.NET.

Model in Visual Basic
Shows the model in Visual Basic.

Home | Contents | Previous | Next