Structured support vector machine
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Classification Techniques in Machine Learning: Applications and Issues Open
Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic …
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Efficient English text classification using selected Machine Learning Techniques Open
Text classification (TC) is an approach used for the classification of any kind of documents for the target category or out. In this paper, we implemented the Support Vector Machines (SVM) model in classifying English text and documents. H…
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An efficient instance selection algorithm to reconstruct training set for support vector machine Open
Support vector machine is a classification model which has been widely used in many nonlinear and high dimensional pattern recognition problems. However, it is inefficient or impracticable to implement support vector machine in dealing wit…
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Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization Open
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters.…
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Particle Swarm Optimization Based Support Vector Machine (P-SVM) for the Segmentation and Classification of Plants Open
With the rapid growth in urbanization and population, it has become an earnest task to nurture and grow plants that are both important in sustaining the nature and the living beings needs. In addition, there is a need for preserving the pl…
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Support Vector Machines and Support Vector Regression Open
In this chapter, the support vector machines (svm) methods are studied. We first point out the origin and popularity of these methods and then we define the hyperplane concept which is the key for building these methods. We derive methods …
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The effect of gamma value on support vector machine performance with different kernels Open
Currently, the support vector machine (SVM) regarded as one of supervised machine learning algorithm that provides analysis of data for classification and regression. This technique is implemented in many fields such as bioinformatics, fac…
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Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine (SVM) for Malware Classification Open
Effective and efficient mitigation of malware is a long-time endeavor in the information security community. The development of an anti-malware system that can counteract an unknown malware is a prolific activity that may benefit several s…
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Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis Open
To overcome the two-class imbalanced classification problem existing in the diagnosis of breast cancer, a hybrid of Random Over Sampling Example, K-means and Support vector machine (RK-SVM) model is proposed which is based on sample select…
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The Development and Application of Support Vector Machine Open
Support Vector Machine(SVM) algorithm has the advantages of complete theory, global optimization, strong adaptability, and good generalization ability because of it on the basis of Statistical Learning Theory’s(SLT). It is a new hot spot i…
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Nonlinear optimization and support vector machines Open
Support vector machine (SVM) is one of the most important class of machine learning models and algorithms, and has been successfully applied in various fields. Nonlinear optimization plays a crucial role in SVM methodology, both in definin…
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Biased support vector machine and weighted-smote in handling class imbalance problem Open
Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy. Support Vector Machine (SVM) is robust and precise method in handling class imba…
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Support Vector Machine – A Large Margin Classifier to Diagnose Skin Illnesses Open
Support Vector Machine (SVM) have been very popular as a large margin classifier due its robust mathematical theory. It has many practical applications in a number of fields such as in bioinformatics, in medical science for diagnosis of di…
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Multi-class Document Classification using Support Vector Machine (SVM) Based on Improved Naïve Bayes Vectorization Technique Open
At present several vectorization approaches are used to transform text documents into a numerical format.A huge number of features converted from text data from a single document take time to process vectorized data with large dimensions.T…
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gensvm: A Generalized Multiclass Support Vector Machine Open
__Abstract__ Traditional extensions of the binary support vector machine (SVM) to multiclass problems are either heuristics or require solving a large dual optimization problem. Here, a generalized multiclass SVM called GenSVM is proposed,…
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Big Data Classification Using the SVM Classifiers with the Modified Particle Swarm Optimization and the SVM Ensembles Open
The problem with development of the support vector machine (SVM) classifiers using modified particle swarm optimization (PSO) algorithm and their ensembles has been considered. Solving this problem would allow fulfilling the high-precision…
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Multisensory Data-Driven Health Degradation Monitoring of Machining Tools by Generalized Multiclass Support Vector Machine Open
Health degradation monitoring of machining tools is of great importance in industrial application field. In this paper, a novel multisensory data-driven health degradation monitoring system schema for the machining tools is proposed by usi…
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Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination Open
Recently, support vector machines, a supervised learning algorithm, have been widely used in the scope of credit risk management. However, noise may increase the complexity of the algorithm building and destroy the performance of classifie…
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A Melanoma Skin Cancer Detection Using Machine Learning Technique: Support Vector Machine Open
In this paper proposed is an easy way to detect the disease and help us to know before something turns out to be serious. The aim of this work is to detect skin cancer. People can get to know what skin disease they are having and what all …
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Hyperspectral Image Classification Based on Non-Parallel Support Vector Machine Open
Support vector machine (SVM) has a good effect in the supervised classification of hyperspectral images. In view of the shortcomings of the existing parallel structure SVM, this article proposes a non-parallel SVM model. Based on the tradi…
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Efficient multi-level lung cancer prediction model using support vector machine classifier Open
This paper aims at the requirement for an interactive learning framework which empowers the successful checking of disorder in a patient. Principal component analysis stands out as an outstanding algorithm to significantly classify the tar…
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A support vector machine method for bid/no bid decision making Open
The bid/no bid decision is an important and complex process, and is impacted by numerous variables that are related to the contractor, project, client, competitors, tender and market conditions. Despite the complexity of bid decision makin…
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Analyzing of salient features and classification of wine type based on quality through various neural network and support vector machine classifiers Open
Wine quality certification is crucial to the wine industry. Indian wine’s superior quality is well-known around the world. Wine quality certification is crucial to the wine industry. Our main objective in this study is to find out a machin…
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Application of machine learning on brain cancer multiclass classification Open
Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics …
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Improved Support Vector Machine Using Multiple SVM-RFE for Cancer Classification Open
Support Vector Machine (SVM) is a machine learning method and widely used in the area of cancer studies especially in microarray data. Common problem related to the microarray data is that the size of genes is essentially larger than the n…
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Clustering categories in support vector machines Open
The support vector machine (SVM) is a state-of-the-art method in supervised classification. In this paper the Cluster Support Vector Machine (CLSVM) methodology is proposed with the aim to increase the sparsity of the SVM classifier in the…
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Black-Box Classifier Interpretation Using Decision Tree and Fuzzy Logic-Based Classifier Implementation Open
Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance.They are applied in various fields such as inductive inferences, classifications, or regres…
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A new model for iris data set classification based on linear support vector machine parameter's optimization Open
Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. On…
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Multi-Class Support Vector Machine via Maximizing Multi-Class Margins Open
Support Vector Machine (SVM) is originally proposed as a binary classification model, and it has already achieved great success in different applications. In reality, it is more often to solve a problem which has more than two classes. So,…
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Machine Learning Algorithm for Classification Open
Recently, machine learning methods have a good performance in the field of classification tasks. Summarizing and comparing the performances of different classifiers in the application of their specific classification tasks has a reference …