Model selection for support vector machine classification
نویسندگان
چکیده
منابع مشابه
Model selection for support vector machine classification
We address the problem of model selection for Support Vector Machine (SVM) classification. For fixed functional form of the kernel, model selection amounts to tuning kernel parameters and the slack penalty coefficient C. We begin by reviewing a recently developed probabilistic framework for SVM classification. An extension to the case of SVMs with quadratic slack penalties is given and a simple...
متن کاملAn Intelligence-Based Model for Supplier Selection Integrating Data Envelopment Analysis and Support Vector Machine
The importance of supplier selection is nowadays highlighted more than ever as companies have realized that efficient supplier selection can significantly improve the performance of their supply chain. In this paper, an integrated model that applies Data Envelopment Analysis (DEA) and Support Vector Machine (SVM) is developed to select efficient suppliers based on their predicted efficiency sco...
متن کاملMargin-based Feature Selection Techniques for Support Vector Machine Classification
Feature selection for classification working in high-dimensional feature spaces can improve generalization accuracy, reduce classifier complexity, and is also useful for identifying the important feature “markers”, e.g., biomarkers in a bioinformatics or biomedical context. For support vector machine (SVM) classification, a widely used feature selection technique is recursive feature eliminatio...
متن کاملA Feature Selection Newton Method for Support Vector Machine Classification
A fast Newton method, that suppresses input space features, is proposed for a linear programming formulation of support vector machine classifiers. The proposed stand-alone method can handle classification problems in very high dimensional spaces, such as 28,032 dimensions, and generates a classifier that depends on very few input features, such as 7 out of the original 28,032. The method can a...
متن کاملCommon Spatial Patterns Feature Extraction and Support Vector Machine Classification for Motor Imagery with the SecondBrain
Recently, a large set of electroencephalography (EEG) data is being generated by several high-quality labs worldwide and is free to be used by all researchers in the world. On the other hand, many neuroscience researchers need these data to study different neural disorders for better diagnosis and evaluating the treatment. However, some format adaptation and pre-processing are necessary before ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neurocomputing
سال: 2003
ISSN: 0925-2312
DOI: 10.1016/s0925-2312(03)00375-8