[PDF] Top 20 Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering
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Applications of Support Vector Machine Based on Boolean Kernel to Spam Filtering
... of spam filtering, support vector machine (SVM) is applied widely, because it is efficient and has high separating ...of support vector machine arithmetic is how to ... See full document
5
Mobile SMS Spam Filtering for Nepali Text Using Naïve Bayesian and Support Vector Machine
... for Spam filter- ing. The most common filtering technique is content-based filtering which uses the actual text of message to de- termine whether it is Spam or ...content-based ... See full document
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Overview of Anti spam filtering Techniques
... to spam problem from different dimensions and directions(Islam and Zhou, 2007, Zhang et ...content based filtering, feature selection methods, bag-of-words, machine learning techniques such as ... See full document
6
Support Vector Machines Parameter Selection Based on Combined Taguchi Method and Staelin Method for E-mail Spam Filtering
... many applications such as function approximation, modeling, forecasting, optimization control, etc and has yielded excellent ...of kernel function is a pivotal factor which determines performance of ...RBF ... See full document
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A novelty approach on Tamil spam text extraction by using texton template based support vector machine and LP boosting classifier
... the spam attacks, phishing attacks and web identity ...words based on semantic of similar words through phonetic ...web based applications. The input images are analyzed based on ... See full document
12
Using Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes
... strategy based on residual mutual information (RMI), higher than second order features embedded in multi-channel vibration measurements can be captured ...these applications. The kernel ICA (KICA) ... See full document
12
Mitigating E-Mail Threats - A Web Content Based Application
... a spam e-mail and a legitimate e-mail using machine learning techniques and the identification of spam and phishing emails are quite ...mails based on specific keywords. The machine ... See full document
6
Sentiment Analysis Based Mining and Summarizing Using SVM-MapReduce
... classification. Support vector machines are a specific type of machine learning algorithm used for many statistical learning problems, such as text classification, spam filtering, face ... See full document
5
Data-Adaptive Kernel Support Vector Machine
... formed based on kernel functions (Hastie et ...the kernel that is crucial to determine the performance of the SVM ...optimal kernel function is driven by the prior knowledge of the data, and ... See full document
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1. Hilbert transform and rbf-kernel based support vector machine synergy for automatic classification of eeg signals
... Epilepsy is a neurological disorder that is caused by the malfunctioning of the nerve cell activity in the brain and is commonly found amongst adults as well as children worldwide. This disease is characterized by ... See full document
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Performance Analysis of Support Vector Machine (SVM) for Optimization of Fuzzy Based Epilepsy Risk Level Classifications Using Different Types of Kernel Functions from EEG Signal Parameters.
... It is noted that one of main assumptions of SVM is that all samples in the training set are independent and identically distributed (i.i.d), however, in many practical engineering applications, the obtained ... See full document
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Survey of Spam Filtering Techniques and Tools, and MapReduce with SVM
... such spam from important mails spam filtering is ...such spam filtering are Naïve Bayesian classification, Support Vector Machine, K Nearest Neighbor, Neural ... See full document
8
The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches
... In order to develop and test prediction models, we ran- domly divided the whole cohort into training and testing cohorts. In this way, the features of the model are identi- fied in the training cohort and then tested in ... See full document
10
Comparative Study of The Performance of Various Classifiers in Labeling Non-Functional Requirements
... The problem of processing requirements documents using natural language processing and machine learn- ing methods has been a research topic for decades [4]. Although non-functional requirements are less de- ... See full document
14
A Support Vector Machine Based Dynamic Network for Visual Speech Recognition Applications
... Several methods have been reported in the literature for visual speech recognition. The adopted methods vary widely with respect to: (1) the feature types, (2) the classifier used, and (3) the class definition. For ... See full document
12
Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
... We used our proposed SVM method with a CAD sys- tem and dental panoramic radiographs to diagnose women with low BMD easily and quickly. The use of the SVM kernel in this study provided a high degree of consis- ... See full document
11
Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine
... of filtering information that is useful from a large pool of information ...collaborative filtering approach in which user data is considered while processing information for the ...classes based on ... See full document
5
ADAPTIVE POWER SYSTEM STABILIZER USING SUPPORT VECTOR MACHINE
... of Support Vector Machine based Power System Stabilizer (SVMPSS) parameters using and sigmoidal kernel is ...Single Machine Infinite Bus (SMIB) system The effect of system ... See full document
6
Applications of Text Clustering Based on Semantic Body for Chinese Spam Filtering
... With the rapid development of Internet application in China, e-mail has become a communicational tool, which plays an increasingly important role in our daily work and life, especially in recent years the rapid ... See full document
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Kernel Based Extreme Learning Machine in Identifying Dermatological Disorders
... Polynomial kernel functions, Radial Basis Function and Exponential chi-square kernel function to diagnose these diseases and obtain good classification accuracy with less learning time compare to ... See full document
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