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0.24/_sources/auto_examples/svm/plot_svm_anova.rst.txt
@@ -62,7 +62,7 @@ that our model achieves best performance when we select around 10% of features.
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# #############################################################################
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# Create a feature-selection transform, a scaler and an instance of SVM that we
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- # combine together to have an full-blown estimator
+ # combine together to have a full-blown estimator
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clf = Pipeline([('anova', SelectPercentile(chi2)),
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('scaler', StandardScaler()),
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('svc', SVC(gamma="auto"))])
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