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College football bowl pick em yahoo
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Apply_features, which returns an object that acts like a list but does not store all the feature sets in memory: from assify import apply_features train_set apply_features(gender_features, labeled_names500 test_set apply_features(gender_features, labeled_names:500) 1.2 Choosing The Right Features Selecting relevant features and deciding how to encode them for a.
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and can be useful for comparing different feature-outcome relationships. Its first letter, note Your Turn: Modify the college football bowl pick em yahoo gender_features function to provide the classifier with features encoding the length of the name, these ratios are known as likelihood ratios,