Support Vector Machine with K-fold Validation to Improve the Industry’s Sustainability Performance Classification

Common 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 ...

Contextual image classification with Support Vector Machine

Chinese Question Classification with Support Vector Machine

______________________________________________________________________________ Abstract. Question classification plays a crucial important role in the question answering system because categorizing a given question is beneficial to identify an answer in the documents. It is the basic and important module of question answering which task is to assign one or several classes to a given question; t...

Support Vector Machine Classification with Indefinite Kernels

We propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our algorithm simultaneously computes support vectors and a proxy kernel matrix used in forming the loss. This can be interpreted as a penalized kernel learning problem where indefinite kernel matrices are treated as a noisy observation...

Incremental Support Vector Machine Classification

Using a recently introduced proximal support vector machine classifier [4], a very fast and simple incremental support vector machine (SVM) classifier is proposed which is capable of modifying an existing linear classifier by both retiring old data and adding new data. A very important feature of the proposed single-pass algorithm , which allows it to handle massive datasets, is that huge block...