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Showing 1 to 5 of 5 for “"classifier combination"”.
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Multiple classifier combination through ensembles and data generation
… training set when training the component classifiers. The DataBoost approach was evaluated against ten data sets, using both decision trees and neural networks as base classifiers. The experiments show promising results, in terms of overall accuracy when compared to a standard benchmarking …
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Multi-source human identification
… developed. The system uses three sources: face classifier, height classifier, and color classifier. In the process of developing this system, classifier combination and the integration of classifer outputs over sequences of data points were studied in detail. The method of classifier combination …
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Minimally-supervised Methods for Arabic Named Entity Recognition
… present a novel approach to Arabic NER using a combination of semi-supervised and distant learning techniques. We used a variety of classifier combination schemes, including the Bayesian Classifier Combination (BCC) procedure, recently proposed for sentiment analysis. According to our results, …
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Morpho-colorimetric and non-parametric analysis in statistical classification of vascular flora
… input for classification process, in which four classifiers have been performed: Linear Discriminant Analysis (LDA), Classification And Regression Trees (CART), Support Vector Machines (SVM) and Naïve Bayes (NB). In order to enhance the classification accuracy an approach of classifier …
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Automatic human face detection in color images
… candidate verification, we developface/nonface classifiers based on the naive Bayesian model, and investigate three feature extraction schemes, namely intensity, projection on face subspace and edge-based. Techniques for improving face/nonface classification are also proposed, including …