The feature subset selection problem is well known in statistics and pattern recognition. However, many of the techniques deal exclusively with features that are continuous, or, make assumptions that do not hold for many practical machine learning algorithms. For example, one common assumption (monotonicity) says that increasing the number of features can never decrease performance.

These disorders are heterogeneous, meaning that they can present differently in different people, and consequently, no one single approach is likely to help all with these conditions. The two disorders share most of the same symptoms and have similar treatments.

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