[PDF] Top 20 Rule Extraction from Support Vector Machines: A Geometric Approach
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Rule Extraction from Support Vector Machines: A Geometric Approach
... Support Vector Machines are a type of popular unsupervised learning method based on statistical learning ...form. Rule extraction, which combines the non-symbolic and symbolic ... See full document
182
Hybrid rule-extraction from support vector machines
... - Rule-extraction from artificial neural networks (ANNs) as well as support vector machines (SVMs) provide explanations for the decisions made by these ...for ... See full document
6
Comprehensible credit scoring models using rule extraction from support vector machines.
... Rule extraction techniques generate classification models that have clear ...model from which they are generated. Since Support Vector Machines are among the best performing ... See full document
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Sentiment recognition by rule extraction from support vector machines
... allows machines to express and recognize emotions, a core component of computer ...as support vector machines (SVMs) have been used successfully for topic detection in documents and speech as ... See full document
8
Rule Extraction from Support Vector Machines: A Geometric Approach. Technical Report
... rules from trained neural networks have been proposed, notably [4], [2], [17], [11], [14], [12], ...directly from the input- output values of the networks, thus treating them as black- ...for rule ... See full document
11
Geometric Approach to Support Vector Machines Learning for Large Datasets
... Figure 7.47 compares the accuracy obtained for different SVM implementations during nested cross-validation training. The accuracy of the algorithms implemented in GSVM tool are usually significantly better than the ... See full document
151
Toward Actionable Support Vector Machines: A Ranking-based Approach
... rules from non-linear SVMs. The idea is as follows: Given a support vector for a class, a hyper-rectangle is constructed using the crossing points of the support vector with the SVM ... See full document
15
Binarized support vector machines
... called rule extraction procedures within SVM (Barakat and Diederich 2004, 2005; Fung et ...a rule extraction method is applied to a classifier, one obtains an alternative clas- sifier that ... See full document
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Ensemble Learning Approach based Rule Extraction from Support Vector Machine Chitra A*, Anto S
... years, support vector machines (SVMs) have shown good performance in a number of application ...as Support Vector Machine (SVM) which is utilized to screen diabetes, and an ensemble ... See full document
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E-quality control: A support vector machines approach
... feature extraction based on vector quantization and SVD techniques were used for improved defect detection with the results outlining the impor- tance of judicious selection and processing of 2D DWT wavelet ... See full document
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FEATURE EXTRACTION TECHNIQUES USING SUPPORT VECTOR MACHINES IN DISEASE PREDICTION
... for Support Vector Machine- Recursive Feature ...embedded approach that recursively removes unimportant features rather than using the weights for ranking criterion as in Relief ...weight ... See full document
8
Clustering Via Supervised Support Vector Machines
... internal approach to SVM (see svm-internal) clustering is only weakly biased towards the shape of the clusters in the input space (the bias is for spherical clusters in the feature space), it still lacks ... See full document
93
Multi-Domain Aspect Extraction Using Support Vector Machines
... one-vs-rest Support Vector Machine (SVM) classifier and a list of carefully selected features are at the core of our supervised machine learning approach for aspect ... See full document
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Areas categorization by operating Support Vector Machines
... years, Support Vector Machines (SVMs) have demonstrated excellent functioning in a variety of area categorization ...learning approach with abundant outcomes in categorization of high ... See full document
9
An improved approach for detection and classification of vehicles in video using support vector machines
... novel approach for car detection and classification is presented, to a whole new level, by devising a system that takes the video of a vehicle as input, detects and classifies the vehicle based on its make and ... See full document
11
On qualitative robustness of support vector machines
... Since support vector machines play an important role in statistical machine learning, investigating their performance in the presence of moderate model violations is a crucial topic — the more so as ... See full document
15
Numerical Experiments with Support Vector Machines
... optimal from the testing point of view region was found in wide range of “C” parameter ...of support vector ...both from analytical and numerical points of ...the support vectors and to ... See full document
33
Nonstationary regression with support vector machines
... the Support Vector Machine (SVM) [11] to regression prob- lems, usually called Support Vector Regression (SVR) [12], is a powerful modelling method with a strong theoretical basis and great ... See full document
15
Rating Companies with Support Vector Machines
... the support vector machine (SVM) – to the field of corporate bankruptcy ...that support vector machines are capable of extracting useful information from financial data although ... See full document
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Predicting Bankruptcy with Support Vector Machines
... the support vector machine (SVM) – to corporate bankruptcy ...that support vector machines are capable of extracting useful infor- mation from financial data, although extensive ... See full document
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