In this paper we evaluate the performance of the highest probability SVM nearest neighbor classifier, which is a combination of the SVM and k-NN classifiers, on a corpus of email messages. To classify a sample the algorithm performs the following actions: for each k in a predefined set {k1, ..., kN} it trains an SVM model on k nearest labelled samples, and uses this model to classify the given ...

The SVM based Recursive Feature Elimination (RFE-SVM) algorithm is a popular technique for feature selection, used in natural language processing and bioinformatics. Recently it was demonstrated that a small regularisation constant C can considerably improve the performance of RFE-SVM on microarray datasets. In this paper we show that further improvements are possible if the explicitly computab...

In this paper, a new method for classifying electronic nose data in rats wound infection detection based on support vector machine (SVM) and wavelet analysis was developed. Signals of the sensors were decomposed using wavelet analysis for feature extraction and a PSO-SVM classifier was developed for pattern recognition. The sensor array was optimized and model parameters were selected to achiev...

Power System Security is a major concern in real time operation. Conventional method of security evaluation consists of performing continuous load flow and transient stability studies by simulation program. This is highly time consuming and infeasible for on-line application. Pattern Recognition (PR) is a promising tool for on-line security evaluation. This paper proposes a Support Vector Machi...

Weed detection using image processing is a progressive research area which can revolutionize crop production and increase efficiency in herbicide usage. A SVM classifier was applied in our research to classify and to detect the weed type for weed scouting and spot weeding purposes. However, parameter fine tuning and feature selection for SVM is a complex procedure that is still an active area o...

We present a subspace approach to face detection with Support Vector Machine (SVMs). A linear SVM classifier is trained as a filter to produce a subspace in which a non-linear SVM classifier with Gaussian kernel is trained for face detection. This makes training easier and results in a very efficient face detection algorithm. Experimental results demonstrate their promising performance compared...

In this paper we present experiments for global polarity classification task of Spanish tweets for TASS 2015 challenge. In our methodology, tweets representation is focused on linguistic and polarity features such as lemmatized words, filter of content words, rules of negation, among others. In addition, different transformations are used (LDA, LSI, and TF-IDF) and combined with a SVM classifie...

A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are op...

We describe a Twitter sentiment analysis system developed by combining a rule-based classifier with supervised learning. We submitted our results for the message-level subtask in SemEval 2015 Task 10, and achieved a F1-score of 57.06%. The rule-based classifier is based on rules that are dependent on the occurrences of emoticons and opinion words in tweets. Whereas, the Support Vector Machine (...

Speech Recognition for Urdu language is an interesting and less developed task. This is primarily due to the fact that linguistic resources such as rich corpus are not available for Urdu. Yet, few attempts have been made for developing Urdu speech recognition frameworks using the traditional approaches such as Hidden Markov Models and Neural Networks. In this work, we investigate the use of thr...