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In this study, the differences among widely used weighting schemes are studied by means of ordering terms according to their discriminative abilities using a recently developed framework which expresses term weights in terms of the ratio and absolute difference of term occurrence probabilities. Having observed that the ordering of terms is dependent on the(More)
A novel framework for termset based feature extraction is proposed for binary text classification. The proposed approach is based on the encoding of the terms within a termset. The ternary codes ‘+1’ and ‘−1’ are used to represent the class that the term supports, whereas ‘0’ denotes no support to any of the classes. Four different encoding schemes are(More)
  • Ahmed Darghaoth, Elvan Yılmaz, Assoc, Salamah Muhammed, Chair, Kömürcügil Hasan +14 others
  • 2013
We certify that we have read this thesis and that in our opinion it is fully adequate in scope and quality as a thesis for the degree of Master of Science in Computer Engineering. ABSTRACT The contamination of a desired signal by noise (undesired signal) is a main problem encountered in many applications. The digital filters with fixed coefficients exhibit(More)
The distribution of documents over two classes in binary text cate-gorization problem is generally uneven where resampling approaches are shown to improve F 1 scores. The improvement achieved is mainly due to the gain in recall where precision may deteriorate. Since precision is the primary concern in some applications, achieving higher F 1 scores with a(More)
The distribution of documents over two classes in binary text categorization problem is generally uneven where resampling approaches are shown to improve F 1 scores. The improvement achieved is mainly due to the gain in recall where precision may deteriorate. Since precision is the primary concern in some applications, achieving higher F 1 scores with a(More)
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