no code implementations • 24 Jun 2017 • Harsha S. Gowda, Mahamad Suhil, D. S. Guru, Lavanya Narayana Raju
A method of labeling unlabeled text documents is presented.
no code implementations • 24 Jun 2017 • Lavanya Narayana Raju, Mahamad Suhil, D. S. Guru, Harsha S. Gowda
A method of converting an imbalanced text corpus into a balanced one is presented.
no code implementations • 16 Oct 2016 • D. S. Guru, Mahamad Suhil
During testing, the terms present in the test document are extracted and the term-class relevance of each term is obtained from the stored knowledgebase.
no code implementations • 12 Sep 2016 • Sumithra R, Mahamad Suhil, D. S. Guru
The results are very promising with 46. 71% and 34% of F-measure using SVM and k-NN classifier respectively and with 61% of F-measure for fusion of SVM and k-NN.
no code implementations • 25 Aug 2016 • D. S. Guru, Mahamad Suhil
The proposed measure estimates the degree of relevance of a given term, in placing an unlabeled document to be a member of a known class, as a product of Class_Term weight and Class_Term density; where the Class_Term weight is the ratio of the number of documents of the class containing the term to the total number of documents containing the term and the Class_Term density is the relative density of occurrence of the term in the class to the total occurrence of the term in the entire population.
no code implementations • 24 Aug 2016 • D. S. Guru, Mahamad Suhil, P. Lolika
Further to reduce the complexity of the process we propose to employ spectral clustering to group related regions together to a single there by achieving reduction in dimension.