Merged the correction to knn.

--HG-- branch : dev rename : examples/ga_knn.py => examples/ga/ga_knn.py rename : examples/knn.py => examples/ga/knn.py
falconzyx · Jan 14, 2013 · 8970008 · 8970008
2 parents 2e33d4f + aad565b
commit 8970008
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/examples/ga/ga_knn.py b/examples/ga/ga_knn.py
@@ -44,7 +44,7 @@
 
 def evalClassifier(individual):
     labels = classifier.predict(trainset[N_TRAIN:], individual)
-    return sum(1 for x, y in zip(labels, trainlabels) if x == y)  / float(len(trainlabels)), \
+    return sum(x == y for x, y in zip(labels, trainlabels[N_TRAIN:]))  / float(len(trainlabels[N_TRAIN:])), \
            sum(individual) / float(classifier.ndim)
 
 creator.create("FitnessMulti", base.Fitness, weights=(1.0, -1.0))
@@ -68,15 +68,15 @@ def main():
     # random.seed(64)
     MU, LAMBDA = 100, 200
     pop = toolbox.population(n=MU)
-    hof = tools.HallOfFame(1)
+    hof = tools.ParetoFront()
     stats = tools.Statistics(lambda ind: ind.fitness.values)
     stats.register("avg", tools.mean)
     stats.register("std", tools.std)
     stats.register("min", min)
     stats.register("max", max)
 
     algorithms.eaMuPlusLambda(pop, toolbox, mu=MU, lambda_=LAMBDA,
-                              cxpb=0.5, mutpb=0.2, ngen=40, 
+                              cxpb=0.7, mutpb=0.3, ngen=40, 
                               stats=stats, halloffame=hof)
 
     return pop, stats, hof

diff --git a/examples/ga/knn.py b/examples/ga/knn.py
@@ -88,7 +88,7 @@ def predict(self, data, features=None):
 def classification_rate(features):
     """Returns the classification rate of the default KNN."""
     labels = _knn.predict(trainset[N_TRAIN:], features)
-    return sum(1 for x, y in zip(labels, trainlabels) if x == y)/float(len(trainlabels))
+    return sum(x == y for x, y in zip(labels, trainlabels[N_TRAIN:]))/float(len(trainlabels[N_TRAIN:]))
 
 if __name__ == "__main__":
     trainset = [[1, 0], [1, 1], [1, 2]]