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Forecasting applications on the stock market attract much interest from researchers in the artificial intelligence field. The problem tackled in this study concerns predicting the direction of change of stock price indices, formulated in terms of binary classification. We use gene expression programming to evolve pools of binary classifiers and investigate several approaches to construct ensembles...
Accurate classification of caller interactions within Interactive Voice Response systems would assist corporations to determine caller behavior within these telephony applications. This paper details the development of such a classification system for a pay beneficiary application. Fuzzy Inference Systems, Multi-Layer Perceptron, Support Vector Machine and ensemble of classifiers were developed. Accuracy,...
Meteorological conditions are crucial for the agricultural production. Rainfall, in particular, can be cited as the most influential by having direct relation with hydric balance. Meteorological satellites that cover the whole earth have been extensively used for the development of statistical and artificial intelligence models for rainfall estimation. However, some of these techniques have flaws...
Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an analysis of the effect of removing irrelevant and redundant features with ensemble classifiers using two datasets from UCI machine learning repository. Accuracy and computational time were evaluated by four base classifiers; NaiveBayes,...
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