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Rule-Based Learning Systems for Support Vector Machines

Haydemar Núñez, Cecilio Angulo, Andreu Català
2006 Neural Processing Letters  
In this article, we propose some methods for deriving symbolic interpretation of data in the form of rule based learning systems by using Support Vector Machines (SVM).  ...  By using support vectors from a learned SVM it is possible in our approach to use any standard Radial Basis Function (RBF) learning technique for the rule extraction, whilst avoiding the overlapping between  ...  Acknowledgment This study was partially supported by the Spanish MCyT grant TIC2002-04371-C02-01.  ... 
doi:10.1007/s11063-006-9007-8 fatcat:fjeqldtvfng6ra7fwn2gepm6ua

Induced Rule-Based Fuzzy Inference System from Support Vector Machine Classifier for Anomalous Propagation Echo Detection

Hansoo Lee, Yeongsang Jeong, Sungshin Kim
2016 International Journal of Machine Learning and Computing  
Further, we can determine the inner structure of the support vector machine. Index Terms-Support vector machine, rule extraction, fuzzy inference system, anomalous propagation echo.  ...  In this paper, we propose a method to make a fuzzy inference system using extracted rules from the support vector machine.  ...  As The observation efficiency of the weather radar is different Induced Rule-Based Fuzzy Inference System from Support Vector Machine Classifier for Anomalous Propagation Echo Detection Hansoo Lee  ... 
doi:10.18178/ijmlc.2016.6.2.579 fatcat:zxytnhaxsfaa5edca6qljitkti

Improving the Interpretability of Support Vector Machines-based Fuzzy Rules [article]

Duc-Hien Nguyen, Manh-Thanh Le
2014 arXiv   pre-print
Support vector machines (SVMs) and fuzzy rule systems are functionally equivalent under some conditions.  ...  Therefore, the learning algorithms developed in the field of support vector machines can be used to adapt the parameters of fuzzy systems.  ...  Extracting fuzzy rules from support vector machine Support vector machine (SVM), which is proposed by Vapnik, is a new machine learning method based on the Statistical Learning Theory and is a useful technique  ... 
arXiv:1408.5246v1 fatcat:3twrru32zjdgzgnq7rtj6pgpbu

Ensemble of Rule Learner and Sequential Minimum Optimization Algorithm for Intrusion Detection System

2019 International Journal of Engineering and Advanced Technology  
The ensemble of Partial Decision Tree and Sequential Minimum optimization algorithm to train support vector machine have used for intrusion detection system.  ...  In this paper, machine learning ensemble have designed and implemented for the intrusion detection system.  ...  In this paper, the ensemble of PART rule learner and SMO based Support Vector Machine base classifiers have used for intrusion detection system.  ... 
doi:10.35940/ijeat.a9559.129219 fatcat:nuede5vtuvcrdh36npmvzn4osi

Application of Support Vector Machine in Fault Diagnosis of Elevator Key Structures

Yan Dou, Lanzhong Guo, Yunbo Li, Yunfei Zhu, W. Deng
2019 MATEC Web of Conferences  
This paper mainly introduces the application of support vector machine in fault diagnosis of elevator key structures.  ...  elevator closed loop control system based on Support Vector Machine The idea of fault diagnosis of elevator closed-loop control system based on support vector machine is to establish support vector machine  ...  the fault diagnosis of the closed-loop control system, firstly, a support vector machine identification model for fault diagnosis is established based on the measurement and known signals in the system  ... 
doi:10.1051/matecconf/201926701008 fatcat:xweoibo6dbatzlj6r4zzwydqhq

Intrusion Detection using Associative Rule and Support Vector Machine

Fadekemi A. Adetoye
2021 International Journal of Computer Applications  
In addition, an intrusion detection model was developed based association rule and support vector machine and performance of the model was evaluated.  ...  General Terms Rule based Intrusion Detection and non-rule-based intrusion detection  ...  figure 1 designates the System architecture for intrusion detection using association rule and support vector machine.  ... 
doi:10.5120/ijca2021920991 fatcat:tecjgyxbbnhpzmstt2tlngxd4a

Automated medical abbreviation detection

MOHD SULAIMAN Ismat, ABDUL KAREEM Sameem, BULGIBA Awang
2021 Zenodo  
The detection model was trained and tested using the decision tree and support vector machine. Results: The domain-specific word embedding gave the best result compared to the FastText and rule-base.  ...  Using Malaysian Cardiology discharge summaries written in English, we compared the results of machine learning approaches to detect abbreviations using rule-based features versus state-of-the-art word  ...  for the Machine Learning.  ... 
doi:10.5281/zenodo.5457478 fatcat:p33zwxdwhnbfrhp5xlmot3ic6y

Analysis of Machine Learning through Support Vector Machine: Catalyst

Pooja Shrimali, K. Venugopalan
2014 International Journal of Computer Applications  
This paper investigates the use of support vector machine (SVM) in machine learning. The purpose of this study is to experiment of SVM in e-learning methodology.  ...  In the article [19] artificial neural network (ANN) has been used to test learners learning capabilities, which is now being replaced by SVM in the present article to understand statistical analysis of  ...  , rule-based methods include a set of rules through training, at the other hand statistical system learn statistical models [26] .  ... 
doi:10.5120/17532-8105 fatcat:ooeaf7npfraz3bdeexqoymjjqy

Artificial Intelligence Techniques for Network Intrusion Detection

Karan Napanda, Harsh Shah, Lakhsmi Kurup
2015 International Journal of Engineering Research and  
It also provides other techniques which can be used for intrusion detection like Naïve Bayes, Decision Tree, K-nearest neighbors and Support Vector Machine.  ...  These techniques were used to classify malicious activity and normal activity and base rules such that necessary actions can be committed to alert and prevent intrusion.  ...  Thus, multiclass support vector machines can be used for classification in the Intrusion Detection System.  ... 
doi:10.17577/ijertv4is110283 fatcat:kbpxtylihjepxees4c2apmidhy

Movie Review analysis using Rule-Based &Support Vector Machines methods

Swati A. Kawathekar
2012 IOSR Journal of Engineering  
This paper combines rule-based classification, supervised learning and machine learning into a new combined method. This method is tested on movie review.  ...  Sentiment analysis is one present day solution for this issue.  ...  SUPPORT VECTOR MACHINES A support vector machine (SVM) is for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis.  ... 
doi:10.9790/3021-0203389391 fatcat:zinatr6db5cx7bgw3mpki2llcu

Teaching Quality Assessment System Based on Support Vector Machine Technology

Wen-xue Huang, Xin Gao, Ning Wang, Yan-chao Yang, Ying Yan
2016 International Journal of Emerging Technologies in Learning (iJET)  
The index value of the pulsed GTAW pool dynamic process by support vector machine inference and support vector machine neural networks is implemented in the teaching quality evaluation system.  ...  The teaching quality assessment system was tested on 30 teachers in a college. The results show that the assessment system is increasingly evidence-based.  ...  Support Vector Machine is a new machine learning method proposed by Literature [5] based on statistical learning theory.  ... 
doi:10.3991/ijet.v11i11.6251 fatcat:a52c2gtx5rgnzos5o5kwvndd5m

Eclectic Rule-Extraction From Support Vector Machines

Nahla Barakat, Joachim Diederich
2008 Zenodo  
In this paper, a novel approach for eclectic rule-extraction from support vector machines is presented.  ...  Support vector machines (SVMs) have shown superior performance compared to other machine learning techniques, especially in classification problems.  ...  Decompositional approaches can be based on the analysis of support vectors generated by the SVM while learning-based approaches learn what the SVM has learned.  ... 
doi:10.5281/zenodo.1055511 fatcat:akpbjgvbj5cz3ghk4qr3kfi2om

Computational Methods for Text Analysis and Text Classification [chapter]

Hercules Dalianis
2018 Clinical Text Mining  
The principles of machine learning-based systems such as Conditional Random Fields (CRF), Support Vector Machines (SVM) and the Weka toolkit supporting several machine learning algorithms and evaluation  ...  In this chapter the differences between rule-based systems and machine learningbased systems along with their respective pros and cons will be explained.  ...  Stanford NER is a well performing system with an elaborate graphical interface, see Fig. 8 Support Vector Machines (SVM) is one of the most effective and popular machine learning algorithms for classification  ... 
doi:10.1007/978-3-319-78503-5_8 fatcat:mrsk7xytujefxj4xfahkc5vco4

A Review on Intrusion Detection System using Artificial Intelligence Approach

Apoorva Deshpande
2018 SMART MOVES JOURNAL IJOSCIENCE  
This paper discusses some commonly used machine learning techniques in Intrusion Detection System and also reviews some of the existing machine learning IDS proposed by researchers at different times.  ...  solution of machine learning.  ...  To reduce the false alarm rate of anomaly-based IDS, many machine learning techniques, including support vector machine (SVM) Feng et al.  ... 
doi:10.24113/ijoscience.v4i8.153 fatcat:hf7fcx2dsjeh7bv76umkgteoya

Adaptive Distributed Intrusion Detection using Hybrid K-means SVM Algorithm

Amit Bhardwaj, Parneet Kaur
2013 International Journal of Computer Applications  
The authors are highly thankful to Dr Maninder Singh, Thapar University, Patiala without whose guidance and support this work would not have been possible.  ...  There are two approaches for taking advantage of k-means clustering algorithm to reduce the number of support vectors used for training the support vector machine.  ...  For example, some neural networks, support vector machines, kmeans clustering etc are used.  ... 
doi:10.5120/12963-0145 fatcat:loxgjxsxxvblxmayafdkgufrwq
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