Differences

This shows you the differences between two versions of the page.

--- code:multi_class [2015/10/05 15:13]
asa created
+++ code:multi_class [2016/10/11 12:57]
asa
@@ Line 5: / Line 5: @@
 <file python multi_class.py>
+import numpy as np
 from sklearn import datasets
-from sklearn.multiclass import OneVsRestClassifier
+from sklearn.multiclass import OneVsRestClassifier,OneVsOneClassifier
-from sklearn.svm import LinearSVC
+from sklearn.svm import LinearSVC,SVC
 from sklearn import cross_validation
+# load the iris dataset:
 iris = datasets.load_iris()
 X, y = iris.data, iris.target
+# prepare cross validation folds
+cv = cross_validation.StratifiedKFold(y, 5, shuffle=True, random_state=0)
+# one-vs-the-rest
 classifier = OneVsRestClassifier(LinearSVC())
+print (np.mean(cross_validation.cross_val_score(classifier, X, y, cv=cv)))
+# one-vs-one
+classifier = OneVsOneClassifier(LinearSVC())
+print (np.mean(cross_validation.cross_val_score(classifier, X, y, cv=cv)))
-print cross_validation.cross_val_score(classifier, X, y, cv=5)
+# does this mean that one-vs-one is better?  not necessarily...
+classifier = OneVsRestClassifier(SVC(C=1, kernel='rbf', gamma=0.5))
+print (np.mean(cross_validation.cross_val_score(classifier, X, y, cv=cv)))
 </file>

CS545 fall 2016