236 lines
5.9 KiB
Plaintext
236 lines
5.9 KiB
Plaintext
Scenario 2 - Epileptic Seizure Classification
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================================================
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Configuration loaded: 3 folds, 2 feature options, 2 radius options.
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Loading dataset from ./Datasets/epileptic_seizure_data.csv ...
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Dataset loaded: 11500 samples, 178 features, 5 classes.
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Splitting data into train/val/test (60/20/20%)...
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-> train: 6900 val: 2300 test: 2300
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Applying z-score normalization...
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GRID SEARCH (features × radius) using 3-fold CV
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[GRID] features= 5, radius=0.50 ...
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-> Fold 1/3 ...
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ANFIS info:
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Number of nodes: 92
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Number of linear parameters: 7
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Number of nonlinear parameters: 70
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Total number of parameters: 77
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 7
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Minimal training RMSE = 1.13032
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Minimal checking RMSE = 1.13236
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Overall Accuracy: 30.61%
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Cohen's Kappa : 0.169
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kappa=0.169 rules=7
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-> Fold 2/3 ...
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ANFIS info:
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Number of nodes: 140
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Number of linear parameters: 11
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Number of nonlinear parameters: 110
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Total number of parameters: 121
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 11
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Minimal training RMSE = 1.12499
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Minimal checking RMSE = 1.15105
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Overall Accuracy: 39.43%
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Cohen's Kappa : 0.289
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kappa=0.289 rules=11
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-> Fold 3/3 ...
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ANFIS info:
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Number of nodes: 128
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Number of linear parameters: 10
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Number of nonlinear parameters: 100
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Total number of parameters: 110
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 10
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Minimal training RMSE = 1.13166
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Minimal checking RMSE = 1.12551
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Overall Accuracy: 34.91%
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Cohen's Kappa : 0.225
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kappa=0.225 rules=10
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-> mean Kappa=0.227 mean rules=9
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[GRID] features= 5, radius=0.75 ...
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-> Fold 1/3 ...
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ANFIS info:
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Number of nodes: 68
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Number of linear parameters: 5
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Number of nonlinear parameters: 50
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Total number of parameters: 55
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 5
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Minimal training RMSE = 1.12389
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Minimal checking RMSE = 1.12597
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Overall Accuracy: 33.17%
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Cohen's Kappa : 0.210
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kappa=0.210 rules=5
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-> Fold 2/3 ...
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ANFIS info:
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Number of nodes: 68
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Number of linear parameters: 5
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Number of nonlinear parameters: 50
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Total number of parameters: 55
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 5
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Minimal training RMSE = 1.15261
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Minimal checking RMSE = 1.16568
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Overall Accuracy: 34.30%
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Cohen's Kappa : 0.240
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kappa=0.240 rules=5
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-> Fold 3/3 ...
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ANFIS info:
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Number of nodes: 68
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Number of linear parameters: 5
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Number of nonlinear parameters: 50
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Total number of parameters: 55
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 5
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Minimal training RMSE = 1.14349
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Minimal checking RMSE = 1.13975
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Overall Accuracy: 34.65%
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Cohen's Kappa : 0.226
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kappa=0.226 rules=5
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-> mean Kappa=0.225 mean rules=5
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[GRID] features= 8, radius=0.50 ...
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-> Fold 1/3 ...
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ANFIS info:
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Number of nodes: 209
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Number of linear parameters: 11
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Number of nonlinear parameters: 176
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Total number of parameters: 187
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 11
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Minimal training RMSE = 1.11568
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Minimal checking RMSE = 1.12592
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Overall Accuracy: 35.26%
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Cohen's Kappa : 0.224
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kappa=0.224 rules=11
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-> Fold 2/3 ...
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ANFIS info:
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Number of nodes: 209
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Number of linear parameters: 11
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Number of nonlinear parameters: 176
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Total number of parameters: 187
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 11
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Minimal training RMSE = 1.08705
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Minimal checking RMSE = 1.11471
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Overall Accuracy: 35.48%
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Cohen's Kappa : 0.226
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kappa=0.226 rules=11
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-> Fold 3/3 ...
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ANFIS info:
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Number of nodes: 209
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Number of linear parameters: 11
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Number of nonlinear parameters: 176
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Total number of parameters: 187
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 11
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Minimal training RMSE = 1.12397
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Minimal checking RMSE = 1.12198
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Overall Accuracy: 35.65%
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Cohen's Kappa : 0.230
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kappa=0.230 rules=11
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-> mean Kappa=0.227 mean rules=11
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[GRID] features= 8, radius=0.75 ...
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-> Fold 1/3 ...
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ANFIS info:
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Number of nodes: 119
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Number of linear parameters: 6
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Number of nonlinear parameters: 96
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Total number of parameters: 102
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 6
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Minimal training RMSE = 1.12245
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Minimal checking RMSE = 1.12803
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Overall Accuracy: 32.70%
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Cohen's Kappa : 0.196
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kappa=0.196 rules=6
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-> Fold 2/3 ...
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ANFIS info:
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Number of nodes: 173
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Number of linear parameters: 9
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Number of nonlinear parameters: 144
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Total number of parameters: 153
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 9
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Minimal training RMSE = 1.10065
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Minimal checking RMSE = 1.12512
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Overall Accuracy: 37.09%
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Cohen's Kappa : 0.251
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kappa=0.251 rules=9
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-> Fold 3/3 ...
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ANFIS info:
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Number of nodes: 101
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Number of linear parameters: 5
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Number of nonlinear parameters: 80
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Total number of parameters: 85
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Number of training data pairs: 4600
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Number of checking data pairs: 2300
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Number of fuzzy rules: 5
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Minimal training RMSE = 1.13562
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Minimal checking RMSE = 1.13557
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Overall Accuracy: 33.00%
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Cohen's Kappa : 0.196
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kappa=0.196 rules=5
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-> mean Kappa=0.214 mean rules=7
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BEST HYPERPARAMS
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features=5 radius=0.50 CV Kappa=0.227 mean rules=9
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Training final model on train+val with best params ...
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ANFIS info:
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Number of nodes: 80
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Number of linear parameters: 6
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Number of nonlinear parameters: 60
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Total number of parameters: 66
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Number of training data pairs: 9200
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Number of checking data pairs: 2300
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Number of fuzzy rules: 6
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Minimal training RMSE = 1.14268
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Minimal checking RMSE = 1.1463
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Final training complete: 6 rules.
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Evaluating on TEST set ...
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Overall Accuracy: 29.78%
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Cohen's Kappa : 0.158
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[TEST RESULTS]
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OA = 29.78 %
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Kappa= 0.158
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Rules= 6
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Generating figures ...
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Done. Figures saved in: figures_scn2
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