Binary Classification: Class A or Not

During feature-selection period, representation using all 55 features in binary classification make the issues clear.

1. Is the specific class representative? Does this class have its idiosyncrasy different from others? However, as figures shown here, combination of different subset of feature sets are required for its discriminability for specific class. For an arbitrary example, rhythmic information for classifying class 1 and class 2.

2. In statistics, an outlier is an observation that is numerically distant from the rest of the data. Statistics derived from data sets that include outliers will often be misleading. I think I need to cut off some bad data in relatively standard procedure. After browsing these 8 figures, #1353 has been dropped from the original one. Thus, for building the robust classifier for each class, this process is necessary.

Thus, further trials for refining my classifiers proceeds!