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A Bahadur Representation of the Linear Support Vector Machine
... The support vector machine has been successful in a variety of ...the support vector machine have been studied quite extensively with a particular attention to its Bayes risk ... See full document
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Distributed Inference for Linear Support Vector Machine
... the support vector machine ...both machine learning and statistics ...the Bahadur representation of linear SVM under the fixed p ...(or linear in) the sample size n ... See full document
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Random Projection for Linear 2 norm Support Vector Machine
... The solving speed for SVMs still needs to improve for high dimension with small sample problems, especially in image classification problems. It is common to use dimensionality reduction methods [5], such as Principal ... See full document
9
LAF: Logic Alignment Free and its application to bacterial genomes classification
... alignment-free vector representations are distance measures, such as the Euclidean dis- tance and the d2 distance ...feature vector representation in combination with supervised machine ... See full document
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A Survey on Different Machine Learning Techniques for Air Quality Forecasting for Urban Air Pollution
... Abstract: The delinquent of air pollution has become a staid concern in developed as well as developing republics. Distressing human’s respiratory and cardiovascular system, air pollution is the origin for increased ... See full document
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Support Vector Machine and Least Square Support Vector Machine Stock Forecasting Models
... GARCH (General Autoregressive Conditional Heteroskedasticity) by Bollerslev is a linear time series prediction method. It is a standard textbook material in econometrics and finance[6]. There are many families of ... See full document
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Sales Forecasting using Linear Regression and Support Vector Machine
... the linear regression produced the confusion matrix thus resulting the compact the precise formation of weights based on characteristics and attributes where as SVM classifies the estimation of probabilistic model ... See full document
7
Comparative Evaluation of Multiple Linear Regression and Support vector Machine aided Linear and Non
... multiple linear regression and SVM aided linear ...aided linear and non-linear regression are from same class of ...in linear and non-linear ... See full document
6
Classification of power disturbances using multilevel support vector Machine
... Power-quality (PQ) monitoring is an essential service that many utilities perform for their industrial and larger commercial customers. Detecting and classifying the different electrical disturbances which can cause PQ ... See full document
5
Forgery Detection of Spliced Images Using Machine Learning Classifiers and color Illumination
... of linear equations instead of a convex quadratic programming (QP) problem for classical ...squares support vector machines (LS-SVM) is a version of SVM that involves equality constraints and works ... See full document
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Online Full Text
... accurate representation of various protein features for homology detection remains a ...hybrid support vector machine method (SVM-hybrid) for protein remote homology detection that combines ... See full document
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A Survey on Intrusion Detection Systems and Classification Techniques
... Support vector machine proposed as an essential technique for intrusion detection system ...a machine learning algorithm which is used for both classification and ...standard support ... See full document
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MACHINE LEARNING TOOLS-AN OVERVIEW
... Recently, Machine learning has great scope in industry business, healthcare, transportation ...using machine learning techniques. As machine learning techniques are applied in areas like robotics, ... See full document
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FORECASTING PROFITABILITY IN EQUITY TRADES USING RANDOM FOREST, SUPPORT VECTOR MACHINE AND XGBOOST
... applying machine learning to forecast direct price value as well as direction of equity and derivative instruments in stock markets ...underlying machine learning approaches used to perform the experiment ... See full document
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Comparative Study of The Performance of Various Classifiers in Labeling Non-Functional Requirements
... Bayes, Support Vector Machine with linear kernel, Linear Logistic Regression, Label Propagation, La- bel Spreading, Decision Tree, Extra Tree, K-Nearest Neighbour and Multi Layer ... See full document
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Hybrid MPI/OpenMP Parallel Linear Support Vector Machine Training
... Another family of approaches to QP optimization are based on interior point method (IPM) technology, which works by delaying the split between active and inactive variables for as long as possible. IPMs generally work ... See full document
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Algebraic perceptron in digital channel equalization
... Like the Support Vector Machine, the Algebraic Perceptron also achieves linear separation in the high dimensional feature space, but with reduced calculation requirem[r] ... See full document
5
FPGA Simulation of Linear and Nonlinear Support Vector Machine
... but always may be difficulties in converting real num- bers to their equivalent logarithmic. Ramirez [4] im- plemented a linear SVM for classification of three- dimensional MRI images. Classification accuracy and ... See full document
9
Dual Random Projection for Linear Support Vector Machine
... Support Vector Machine (SVM) [1] has the advantage of dealing with small sample, non-linear data, and high-dimensional pattern ...large-scale machine learning, and the Random ... See full document
8
Ramp Loss Linear Programming Support Vector Machine
... This work was supported in part by the scholarship of the Flemish Government; Research Council KUL: GOA/11/05 Ambiorics, GOA/10/09 MaNet, CoE EF/05/006 Optimization in Engineering (OPTEC), IOF-SCORES4CHEM, several ... See full document
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