Classifier Performances For Credit Risk Analysis Год выпуска: 2012Автор: Erkan CetinerИздательство: LAP Lambert Academic PublishingСтраниц: 72ISBN: 9783848482030Описание This work is prepared for a Master Research Thesis. The main objective of the work is gathering single classification techniques together as one unique hybrid classifier. Experiments made on different data-sets and results are compared in terms of accuracy and precision. Logistic regression, support vector machines, artificial neural networks and naive bayes approach are examined throughout the research. A hybrid model based on average weighting mechanism developed by using those single classifiers.
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Людмила, 18.02 Я защитилась на отлично! Спасибо Вам огромное!! Очень ответственно и добропорядочно подошли к работе! Многие получали свои дипломы, а что касалось доработок, то их просто кидали. Я очень Вам благодарная, желаю Вам успехов в работе, здоровья Вам и вашим близким и всего всего!! Побольше бы таких порядочных людей!! Спасибо!!! :))))
