TY  - JOUR
T1  - Classifier Using Conceptual Granulation and Equal Partition Approach
AU - Malathi, D. AU - Valarmathy, S. 
JO  - International Journal of Soft Computing
VL  - 9
IS  - 3
SP  - 178
EP  - 182
PY  - 2014
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2014.178.182
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2014.178.182
KW  - Domain classifier
KW  -concept granulation
KW  -equal partition
KW  -global set
KW  -eye
AB  - This study presents a systematic approach for the classification of large 
  corpus based on concept granulation and equal partition approach. The proposed 
  research has three main processes which are the preprocessing treatments to 
  text documents, feature extraction and finally the classification. The proposed 
  approach is concentrated in the feature extraction phase. Almost bird eye view 
  like approach is the feature extraction method. So, the proposed research concept 
  granulation and equal partition approach has been named as Immune Term (TIM) 
  which finds the immunized terms from the information system. At first, documents 
  are preprocessed from text to numerical form, i.e., word frequency is calculated 
  for each document. Second, sets of features are extracted using TIM. In the 
  third step, the TIM treated feature is introduced to Principal Component Analysis 
  (PCA) and Latent Semantic Indexing (LSI) for global set extraction or dimension 
  reduction. Finally, Naive Bayes (NB) and Support Vector Machine (SVM) are used 
  to classify the documents. The proposed research seems to be fruitful when compared 
  to the conventional word frequency approach.
ER  -