Searching for Rule Extraction From Support Vector Machines A Sequential Covering Approach information? Find all needed info by using official links provided below.
https://eprints.qut.edu.au/114234
The proposed method extracts rules directly from the support vectors (SVs) of a trained SVM using a modified sequential covering algorithm. Rules are generated based on an ordered search of the most discriminative features, as measured by interclass separation.Cited by: 94
https://www.researchgate.net/publication/3297716_Rule_Extraction_from_Support_Vector_Machines_A_Sequential_Covering_Approach
The proposed method extracts rules directly from the support vectors (SVs) of a trained SVM using a modified sequential covering algorithm. Rules are generated based on an ordered search of the...
https://www.infona.pl/resource/bwmeta1.element.ieee-art-000004161896
In this paper, we propose a novel algorithm for rule extraction from support vector machines (SVMs), termed SQRex-SVM. The proposed method extracts rules directly from the support vectors (SVs) of a trained SVM using a modified sequential covering algorithm. Rules are generated based on an ordered search of the most discriminative features, as measured by interclass separation. Rule ...Cited by: 94
https://www.sciencedirect.com/science/article/pii/S0925231210001591
Sequential covering rule extraction. ... A.P. BradleyRule extraction from support vector machines: a sequential covering approach. IEEE Transactions on Knowledge and Data Engineering, 19 (2007), pp. 729-741 ... D. Martens, J. Huysmans, R. Setiono, J. Vanthienen, B. BaesensRule extraction from support vector machines: an overview of issues and ...Cited by: 174
https://www.sciencedirect.com/science/article/pii/S0957417419302593
A rule extraction approach from support vector machines for diagnosing hypertension among diabetics. ... N.H. Barakat, A.P. BradleyRule extraction from support vector machines: A sequential covering approach. IEEE Transactions on Knowledge and Data Engineering, 19 (6) (2007), pp. 729-741, 10.1109/TKDE.2007.190610.Cited by: 2
http://www.applieddatamining.com/cms/?q=research/rule-extraction
Rule extraction is a techinque designed to remedy this, which extracts comprehensible rules that mimic the decisions made by the black box model. ALPA-R. ... Rule Evaluation for Metaheuristic-based Sequential Covering Algorithms. ... Support vector machines (SVMs) are currently state-of-the-art for the classification task and, generally ...
https://link.springer.com/chapter/10.1007%2F978-3-642-15387-7_50
Abstract. Despite superior generalization performance Support vector machines (SVMs) generate black box models. The process of converting such opaque models into transparent model is often regarded as rule extraction.This paper presents a new approach for rule extraction from SVMs using modified active learning based approach (mALBA), to predict churn in bank credit cards.Cited by: 7
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.5132
Rule extraction describes a pattern or relationships between input features and output class labels directly from the data. This paper utilizes two different techniques for rule extraction. Sequential covering Rule Extraction and the eclectic methods are used to turn the SVM black box into a more intelligible model.
https://www.researchgate.net/publication/5503400_Minerva_Sequential_Covering_for_Rule_Extraction
In this paper, a novel approach for rule-extraction from support vector machines is presented. This approach handles rule-extraction as a learning task, which proceeds in two steps.
https://www.hausarbeiten.de/document/193686
Oct 12, 2011 · Rule Extraction from Support Vector Machine - Applications to Banking and Finance - Mohammed Farquad - Doktorarbeit / Dissertation - Informatik - Angewandte Informatik - Publizieren Sie Ihre Hausarbeiten, Referate, Essays, Bachelorarbeit oder MasterarbeitAuthor: Mohammed Farquad (Autor)
How to find Rule Extraction From Support Vector Machines A Sequential Covering Approach information?
Follow the instuctions below:
- Choose an official link provided above.
- Click on it.
- Find company email address & contact them via email
- Find company phone & make a call.
- Find company address & visit their office.
