SVM Algorithm
Text Detection Model Based on Parallel SVM Algorithm
... distributed algorithm can significantly improve the operational efficiency, and the SVM algorithm developed by the MATLAB par- allel computing toolbox is applied to achieve 98% of the model ...
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A SVM Algorithm for Investigation of Tri-Accelerometer Based Falling Data
... Abstract Falling in elderly people is one of the main reasons causing serious injuries and increasing the risk of early death. Moreover, it can result in psychological problems from fear of falling. An automatic fall ...
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SVM Algorithm for the Robotic Detection of Retinal Hemorrhage in Fundus Images
... Abstract Many important eye diseases as well as systemic diseases manifest themselves in the retina. Diabetic retinopathy is a vascular disease of the retina which affects patients with diabetes mellitus. A number of ...
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High Performance of Polynomial Kernel at SVM Algorithm for Sentiment Analysis
... However, classification of sentiment is a special case of document categorization with two classes such as positive and negative. In this kind classification, it is involved to analyze sentiment for comment of the ...
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Curvelet Image Fusion using Neural Network and SVM Algorithm
... and SVM which represents edges better than wavelets and since edges play a vital role in image understanding and one great approach to enhance spatial resolution is to upgrade the edges then Curvelet-based image ...
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Gender Recognition from Model’s Face Using SVM Algorithm
... Abstract - This paper presents a method for Gender Recognition using Support Vector Machine (SVM).This System consists of two stages – Feature Extraction and SVM Classification. In Feature Extraction we ...
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Multimodel Document Summarization K-SVM Algorithm
... DBSCAN algorithm for clustering the documents. The DBSCAN algorithm requires only one input parameter and helps the user in determining the actual value for ...this algorithm. For large spatial ...
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Dynamic Allocation of Cloud Resources Using Skewness and SVM Algorithm
... appropriated SVM techniques in these works unite and increment test ...disseminated SVM strategies is rest information lumping then parallel usage of SVM ...
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Comparison: KNN & SVM Algorithm
... Our main goal is to find a line that uniquely divides the data into two regions. Such data which can be divided into two with a straight line (or hyperplanes in higher dimensions) is called Linear Separable. In above ...
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Evaluating the performance of SVM and Apriori Algorithms for Bigdata Sudha M 1, Saravana Kumar E2
... Data classification is the process of organizing data into categories for its most effective and efficient use. The goal of classification is to accurately predict the target class for each case in the data. ...
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Application of Gist SVM in Cancer Detection
... Support vector machines are a set of related supervised learning methods used for classification and regression. Linear classification when used for classification, the SVM algorithm creates a hyper plane ...
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Zero-Day Aware Decision Fusion-Based Model for Crypto-Ransomware Early Detection
... One-Class SVM (OC-SVM) algorithm. In this algorithm, the training data has only one type of ...OC- SVM determines a hyper sphere of minimum volume that covers all the training points ...
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Research on the Detection of Network Intrusion Prevention With Svm Based Optimization Algorithm
... of SVM in intrusion detection, it was optimized by the WAO algorithm in this study, and then it was verified by KDD CUP99 data ...IWAO- SVM algorithm had excellent accuracy in the ...
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Sentiment Analysis of Tweets using Rapid Miner Tool
... Bayes, SVM, are applied on data and then the results obtained are ...The SVM algorithm proved to be more accurate compared to the other two algorithms ...
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Study on A Rolling Prediction Model of Power System Load Forecasting Based on Evolutionary SVM
... (SVM) algorithm based time series. The algorithm would resolve how short term power load could be forecasted accurately and ...The algorithm avoided traditional model of SVM to control ...
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Anomaly Intrusion Detection based on a Hybrid Classification Algorithm (GSVM)
... the SVM classifier by detecting the subset of the best values of the kernel parameters for the SVM ...search algorithm to provide a proper ...
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IMAGE FUSION ALGORITHM USING SVM IN CURVELET DOMAIN
... Abstract: This paper displays a novel picture combination strategy appropriate for container honing of multispectral (MS) groups, taking into account multi-determination examination. The low-determination MS groups are ...
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Product recommendations using Data Mining and Machine Learning algorithms
... (SVM) algorithm to predict the similar food products based on the items bought and recommended it to the ...The SVM is implemented using R- Studio and R ...
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Multi-Output Least Square Support Vector Machine for the Reconstruction of Perfect Electric Conductor Below Rough Surface
... Abstract—To save the computation time and improve the accuracy of reconstruction results by support vector machine (SVM), a multi-output least square SVM (LS-SVM) algorithm is proposed to ...
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An Integrated Intrusion Detection System by Combining SVM with AdaBoost
... Single SVM algorithm has certain genera- lization ability for small sample, but for the problem of intrusion detection, its accuracy is still not ...on SVM. The principle is: using the SVM ...
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