Classification-and-Action-Rule-Extraction-using-Fragile-State-Index/BayesNet.txt at main · aarshg28/Classification-and-Action-Rule-Extraction-using-Fragile-State-Index · GitHub

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BayesNet:

=== Run information ===

Scheme:       weka.classifiers.bayes.BayesNet -D -Q weka.classifiers.bayes.net.search.local.K2 -- -P 1 -S BAYES -E weka.classifiers.bayes.net.estimate.SimpleEstimator -- -A 0.5
Relation:     Group-14-Original-weka.filters.unsupervised.attribute.Discretize-B10-M-1.0-Rfirst-last-precision6
Instances:    178
Attributes:   17
              Country
              Year
              Rank
              Total
              C1: Security Apparatus
              C2: Factionalized Elites
              C3: Group Grievance
              E1: Economy
              E2: Economic Inequality
              E3: Human Flight and Brain Drain
              P1: State Legitimacy
              P2: Public Services
              P3: Human Rights
              S1: Demographic Pressures
              S2: Refugees and IDPs
              X1: External Intervention
              Fragile State Index
Test mode:    10-fold cross-validation

=== Classifier model (full training set) ===

Bayes Network Classifier
not using ADTree
#attributes=17 #classindex=16
Network structure (nodes followed by parents)
Country(178): Fragile State Index
Year(1): Fragile State Index
Rank(164): Fragile State Index
Total(10): Fragile State Index
C1: Security Apparatus(10): Fragile State Index
C2: Factionalized Elites(10): Fragile State Index
C3: Group Grievance(10): Fragile State Index
E1: Economy(10): Fragile State Index
E2: Economic Inequality(10): Fragile State Index
E3: Human Flight and Brain Drain(10): Fragile State Index
P1: State Legitimacy(10): Fragile State Index
P2: Public Services(10): Fragile State Index
P3: Human Rights(10): Fragile State Index
S1: Demographic Pressures(10): Fragile State Index
S2: Refugees and IDPs(10): Fragile State Index
X1: External Intervention(10): Fragile State Index
Fragile State Index(4):
LogScore Bayes: -6501.086836682742
LogScore BDeu: -18701.447509520644
LogScore MDL: -14782.581726073686
LogScore ENTROPY: -10038.658885781277
LogScore AIC: -11869.658885781279


Time taken to build model: 0.02 seconds

=== Stratified cross-validation ===
=== Summary ===

Correctly Classified Instances         165               92.6966 %
Incorrectly Classified Instances        13                7.3034 %
Kappa statistic                          0.8893
Mean absolute error                      0.0372
Root mean squared error                  0.1591
Relative absolute error                 11.2996 %
Root relative squared error             39.254  %
Total Number of Instances              178

=== Detailed Accuracy By Class ===

                 TP Rate  FP Rate  Precision  Recall   F-Measure  MCC      ROC Area  PRC Area  Class
                 0.943    0.035    0.868      0.943    0.904      0.881    0.997     0.988     Alert
                 0.944    0.045    0.955      0.944    0.949      0.899    0.995     0.995     Warning
                 0.872    0.007    0.971      0.872    0.919      0.900    0.997     0.989     Stable
                 0.933    0.018    0.824      0.933    0.875      0.865    0.999     0.989     Sustainable
Weighted Avg.    0.927    0.032    0.930      0.927    0.927      0.893    0.996     0.992

=== Confusion Matrix ===

  a  b  c  d   <-- classified as
 33  2  0  0 |  a = Alert
  5 84  0  0 |  b = Warning
  0  2 34  3 |  c = Stable
  0  0  1 14 |  d = Sustainable