Changes between Version 23 and Version 24 of UsersSamples

Timestamp:

02/22/11 17:31:18 (13 years ago)

Author:

gkronber

Comment:

linked to samples in SVN repository

UsersSamples

@@ -186 +186 @@
 [=#GPArtificialAnt]
 === Genetic programming - Artificial Ant Problem ===
-[attachment:SGP_SantaFe.hl]
+[export:/misc/samples/GP_ArtificialAnt-SantaFe.hl GP_ArtificialAnt-SantaFe.hl]
 [[Image(SantaFe Result.png, width=500, right, margin-right=30, margin-left=30)]]
 
@@ -222 +222 @@
 [=#GPSymbolicRegressionBostonHousing]
 === Genetic programming - Symbolic Regression (Boston Housing)===
-[attachment:SGP_SymbReg-Boston-Housing.hl]
+[export:/misc/samples/GP_Regression-Boston-Housing.hl GP_Regression-Boston-Housing.hl]
 
 Example for a simple genetic programming algorithm to create a regression model for the estimation of the median value of houses in a certain in the Boston area based on other parameters of that region. The original dataset was downloaded from http://archive.ics.uci.edu/ml/datasets/Housing. 
@@ -250 +250 @@
 [=#GPSymbolicRegressionTower]
 === Genetic programming - Symbolic Regression (Tower)===
-[attachment:SGP_SymbReg.hl]
+[export:/misc/samples/GP_Regression-TowerResponse.hl GP_Regression-TowerResponse.hl]
 
 Example for a simple genetic programming algorithm to create a regression model for the estimation of a product quality parameter in an industrial chemical process. The original dataset was downloaded from http://vanillamodeling.com/realproblems.html.
@@ -266 +266 @@
 [=#GPSymbolicRegressionMackeyGlass]
 === Genetic programming - Symbolic Regression (Mackey-Glass)===
-[attachment:SGP_SymbReg-Mackey-Glass.hl]
+[export:/misc/samples/GP_Regression-Mackey-Glass.hl GP_Regression-Mackey-Glass.hl]
 
 Example for a simple genetic programming algorithm to create a dynamic model for the one-step prediction of the chaotic Mackey Glass (T=17) time series. The original dataset was downloaded from http://www.bme.ogi.edu/~ericwan/data.html.
@@ -283 +283 @@
 [=#GPSymbolicClassificationWisconsin]
 === Genetic programming - Symbolic Classification (Wisconsin)===
-[attachment:SGP_Classification-WDPC.hl]
+[export:/misc/samples/GP_Classification-WisconsinDiagnostic.hl GP_Classification-WisconsinDiagnostic.hl]
 
 Example for a simple genetic programming algorithm to create a classification model for the estimation of malignant or benign tumor diagnosis based on features extracted through analysis of tumorous cells in a tissue sample. The original dataset was downloaded from the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)). The algorithm uses all available GP manipulation operators, single-point cross-over and squared Pearson's correlation coefficient evaluation.
@@ -293 +293 @@
 [=#GPSymbolicRegressionMammography]
 === Genetic programming - Symbolic Classification (Mammography)===
-[attachment:SGP_SymbClass_Mammographic.hl]
+[export:/misc/samples/GP_Classification-Mammography.hl GP_Classification-Mammography.hl]
 
  A genetic programming algorithm to create a classification model for the prediction of malignant or benign tumor diagnosis based on features extracted through a non-invasive mammography breast cancer screening. Original dataset stems from the UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass).
@@ -301 +301 @@
 [=#GPBooleanEvenParity4]
 === Genetic Programming - Even Parity (4 inputs) ===
-[attachment:SGP_Boolean-Even-Parity-4.hl]
+[export:/misc/samples/Boolean-Even-Parity-4.hl GP_Boolean-Even-Parity-4.hl]
 
  A genetic programming algorithm to synthesize the boolean even parity function with 4 binary inputs
@@ -321 +321 @@
 [=#GPBooleanMultiplexer11]
 === Genetic Programming - Multiplexer (11 inputs) ===
-[attachment:SGP_Boolean-Multiplexer-11.hl]
+[export:/misc/samples/GP_Boolean-Multiplexer-11.hl GP_Boolean-Multiplexer-11.hl]
 
  A genetic programming algorithm to synthesize the boolean multiplexer function with 11 binary inputs