نتایج جستجو برای: support vector machine classifier

تعداد نتایج: 1054694  

2013
Deepak Kumar Vishwakarma Anurag Jain

For a long decade clustering faced a problem of noise and outliers. Support Vector Clustering is one of the techniques in pattern recognition. Support Vector Clustering is Kernel-Based Clustering. Division of patterns, data items, and feature vectors into groups (clusters) is a complicated task since clustering does not assume any prior knowledge, which are the clusters to be searched for. Nois...

Journal: :journal of advances in computer research 2015
maziar kazemi muhammad yousefnezhad saber nourian

classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

Journal: :journal of chemical health risks 0
alireza jalali department of chemistry, college of basic sciences, shahrood branch, islamic azad university, shahrood, iran mehdi nekoei department of chemistry, college of basic sciences, shahrood branch, islamic azad university, shahrood, iran majid mohammadhosseini department of chemistry, college of basic sciences, shahrood branch, islamic azad university, shahrood, iran

a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

2008
Rogério G. Negri Eliana Pantaleão

Support vector machine classifiers are widely used in pattern recognition applications. Contextual information can improve the classifier accuracy for image classification. The autocorrelation function can be used to estimate how relevant the neighborhood information is for a pixel classification. This paper proposes a support vector machine classifier that uses contextual information of the di...

2012
Sandeep Kumar Zeeshan Khan Anurag Jain

Unclassified region decreases the efficiency and performance of multi-class support vector machine. The proper selection of feature sub set reduced the unclassified region of multi-class support vector machine. Now a day’s multi-class classification are widely used in image classification. The feature selection or mapping of data one space to another space creates diversity of outlier and noise...

2002
Glenn Fung Olvi L. Mangasarian Jude W. Shavlik

Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a linear support vector machine classifier. The resulting formulation leads to a linear program that can be solved efficiently. Real world examples, from DNA sequencing and breast cancer prognosis, demonstrate the effectiveness of the proposed method. Numerical...

2012
Maria José Santofimia Romero Xavier del Toro Jesús Barba Julio Dondo Francisca Romero Patricia Navas Ana Rubio Juan Carlos López

This work presents a recognition system for epileptiform abnormalities based on electroencephalogram (EEG) analysis. The proposed system combines a Support Vector Machine classifier automatically trained by an implementation of machine learning approach known as Bag of Words.

2016
Muzaffar Khan Jai Karan Singh Mukesh Tiwari

Electromyographic (EMG) signal provide a significant source of information for diagnosis, treatment and management of neuromuscular disorders.Neuromuscular diseases changes, the shape and characteristics of the motor unit action potentials (MUAPs). The MUAPs detected from myopathic patients are characterized by high frequency contents, low peak-to-peak amplitude and MUAPs neuropathic patients a...

Journal: :journal of medical signals and sensors 0
fatemeh ghofrani mohammad sadegh helfroush mahmoud rashidpour kamran kazemi

in this paper a novel fuzzy scheme for medical x-ray image classification is presented. in this method, any image is partitioned in to 25 overlapping subimages and then shape-texture features are extracted from shape and directional information extracted from any subimage. in the classification stage, we apply a fuzzy membership to any subimage with respect to euclidean distance between feature...

2008
Iñaki Alegria Lluís Màrquez Kepa Sarasola Arantza Casillas Arantza Díaz de Ilarraza Jon Igartua Gorka Labaka Mikel Lersundi

Constructing a classifier that distinguishes machine translations from human translations is a promising approach to automatically evaluating machine-translated sentences. We developed a classifier with this approach that distinguishes translations based on word-alignment distributions between source sentences and human/machine translations. We used Support Vector Machines as machinelearning al...

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