نتایج جستجو برای: support vector machine model
تعداد نتایج: 2899838 فیلتر نتایج به سال:
The use of artificial intelligence in the process of diagnosing heart disease has been considered by researchers for many years. In this paper, an efficient method for selecting appropriate features extracted from electrocardiogram (ECG) signals, based on a genetic algorithm for use in an ensemble multi-kernel support vector machine classifiers, each of which is based on an optimized genetic al...
Mealiness degrades the quality of apples and plays an important role in fruit market. Therefore, the use of reliable and rapid sensing techniques for nondestructive measurement and sorting of fruits is necessary. In this study, the potential of acoustic signals of rolling apples on an inclined plate as a new technique for nondestructive detection of Red Delicious apple mealiness was investigate...
A model selection method based on tabu search is proposed to build support vector machines (binary decision functions) of reduced complexity and efficient generalization. The aim is to build a fast and efficient support vector machines classifier. A criterion is defined to evaluate the decision function quality which blends recognition rate and the complexity of a binary decision functions toge...
Social networking websites are used by millions of people around the world. People express their views, opinions and share current topics. Millions of data generated every day. It’s a good platform to connect with the people. Now a day’s spammers used this platform to advertise spam content on the social networking websites. The proposed system used to classify tweets into different groups as s...
Introduction: Since the delay or mistake in the diagnosis of mood disorders due to the similarity of their symptoms hinders effective treatment, this study aimed to accurately diagnose mood disorders including psychosis, autism, personality disorder, bipolar, depression, and schizophrenia, through modeling and analyzing patients' data. Method: Data collected in this applied developmental resear...
This technical report provides an overview on the support vector machines that have been designed during the recent years for the identification of microRNA sequences. Our aim is to arrive in the end to identify potential ways in which the quality of such machine learning methods could be further improved, knowing that the rate of false positves they produce is still too high.
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