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A Rough Set Based Feature Selection on KDD CUP 99 Data Set
Vinod Rampure,Akhilesh Tiwari 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.1
In the present era as internet is growing with exponential pace, computer security has become a critical issue. In recent times data mining and machine learning have been researched extensively for intrusion detection with the aim of improving the accuracy of detection classifier. KDD CUP’ 99 Data set is the most widely used dataset in research domain. Selecting important feature on the basis of rough set based feature selection approach have lead to a simplification of the problem, faster and more accurate detection rates. In this paper, we presented an efficient approach for detecting relevant features from the KDD CUP’99 Data set.
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A Rough Set Based Classification Model for the Generation of Decision Rules
Vinod Rampure,Akhilesh Tiwari 보안공학연구지원센터 2014 International Journal of Database Theory and Appli Vol.7 No.5
This paper introduces a very important classification aspect for the analysis of huge amount of data stored in databases and other repositories. Numerous classification models are available in the literature, to predict the class of objects whose class level is unknown. Literature reveals that most of the available models are not capable in handling imperfect data. In view of this, present paper proposes a new rough set based classification model to derive the classification (IF-THEN) rules. Furthermore, developed model has been applied to handle bank-loan applications database as either safe, unsafe or risky. However, proposed model can also be used for the analysis of data from other domains.
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Ara, Syeda Arshiya,Arora, Vini,Zakaullah, Syed,Raheel, Syed Ahmed,Rampure, Prakash,Ashraf, Sajna Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.12
Background: Oral submucosal fibrosis (OSMF) is one of the most prevalent premalignant conditions in India which is easy to diagnose but difficult to manage. At present it is considered as irreversible and incurable. It has also been referred to as an epidemic in India. Aims and Objectives: To correlate the frequency and duration of habits with clinical staging, functional staging and histopathological grading and to correlate the clinical and functional staging with histopathological grading. Materials and Methods: The study included a total of 90 subjects, 80 with OSMF in the experimental group and 10 patients in the control group. Patient personal history was recorded with chewing habits, including frequency and duration of chewing. The site of keeping the quid, time duration and whether he/she swallows it or spits it were also noted. Clinical staging was done on the presence of palpable fibrous bands. Functional staging was accomplished by measuring mouth opening. Incisional biopsy was done for all the patients for histopathological examination. Histopathological grading was according to Pindborg and Sirsat. Results: The experimental group comprised 71 males and 9 females, the majority of which were in the age group of 21-30 years. Correlation of habits with clinical staging, functional staging and histopathological grading were significant (p<0.05). Clinical and functional staging did not correlate with histopathological grading, but the correlation of clinical and functional staging was highly significant (p<0.01). Conclusions: The widespread habit of chewing gutkha is a major risk factor for OSMF, especially in the younger age group. In this study, it was found that with increase in the duration and frequency of the habit the severity of the disease increased.
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