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Feature selection in the data with different types of feature values, i.e., the heterogeneous or mixed data, is especially of practical importance because such types of data sets widely exist in real world. The key issue for feature selection in mixed data is how to properly deal with different types of the features or attributes in the data set. Motivated by the fuzzy rough set theory which allows...
In classification tasks, active learning is often used to select out a set of informative examples from a big unlabeled dataset. The objective is to learn a classification pattern that can accurately predict labels of new examples by using the selection result which is expected to contain as few examples as possible. The selection of informative examples also reduces the manual effort for labeling,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.