The concept of classification is used and examined by the scientific community
for hundreds of years. In this historical process, different methods and algorithms
have been developed and used.
Today, although the classification algorithms in literature use different methods,
they are acting on a similar basis. This basis is setting the desired data into classes
by using defined properties, with a different discourse / an effort to establish a
relationship between known features with unknown result. This study was
intended to bring a different perspective to this common basis.
In this study, not only the basic features of data are used, the class of the data is
also included as a parameter. The aim of this method is also using the information
in the algorithm that come from a known value. In other words, the class, in which
the data is included, is evaluated as an input and the data set is transferred to a
higher dimensional space which is a new working environment. In this new
environment it is not a classification problem anymore, but a clustering problem.
Although this logic is similar with Kernel Methods, the methodologies are
different from the way that how they transform the working space. In the
projected new space, the clusters based on calculations performed with the
Mahalanobis Distance are evaluated in original space with two different heuristics
which are center-based and KNN-based algorithm. In both heuristics, increase in
classification success rates achieved by this methodology. For center based
algorithm, which is more sensitive to new input parameter, up to 8% of
enhancement is observed.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612852/index.pdf |
| Date | 01 January 2011 |
| Creators | Durak, Bahadir |
| Contributors | Iyigun, Cem |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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