نتایج جستجو برای: support vector machine classifier
تعداد نتایج: 1054694 فیلتر نتایج به سال:
The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that time. Requiring that the perceptron updates its internal state whenever the normalized margin of a pattern is found not to exceed a certain fraction of this dynamic upper bound we construct a new approximate maximum ...
Sentiment polarity classification is perhaps the most widely studied topic. It classifies an opinionated document as expressing a positive or negative opinion. In this paper, using movie review dataset, we perform a comparative study with different single kind linguistic features and the combinations of these features. We find that the classic topicbased classifier(Naive Bayes and Support Vecto...
This paper describes the problem of classifying opinions expressed into sentences. The system must categorize them as opinionated or factual. To achieve this objective, we have used a Naïve Bayes approach and Support Vector Machines. As a new categorization model, we suggest using a normalized score (Z score) based on a specific vocabulary. Using a NTCIR test collection, our evaluations demonst...
Through the analysis of one-vs.-one, one-vs.-rest and the decision tree mechanism of binary support vector machine emotion classifiers, a method based on feature-driven hierarchical support vector machine is proposed for speech emotion recognition. For each layer, classifier used different feature parameters to drive its performance, and each emotion is subdivided layer by layer. This method di...
Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. Well log data is an alternative approach for prediction of pe...
This paper proposes a PAC-Bayes bound to measure the performance of Support Vector Machine (SVM) classifiers. The bound is based on learning a prior over the distribution of classifiers with a part of the training samples. Experimental work shows that this bound is tighter than the original PAC-Bayes, resulting in an enhancement of the predictive capabilities of the PAC-Bayes bound. In addition...
We design a method for weighting linear support vector machine classifiers or random hyperplanes, to obtain classifiers whose accuracy is comparable to the accuracy of a non-linear support vector machine classifier, and whose results can be readily visualized. We conduct a simulation study to examine how our weighted linear classifiers behave in the presence of known structure. The results show...
The problem of automatic classification of seven types of eating conditions from speech is considered. Based on the confusion among different eating conditions from a seven class support vector machine (SVM) classifier, a hierarchical SVM classifier is designed. Experiments on the iHEARu-EAT database show that the hierarchical classifier results in a better classification accuracy compared to a...
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