منابع مشابه
Conservative Noise Filters
Noisy training data have a huge negative impact on machine learning algorithms. Noise-filtering algorithms have been proposed to eliminate such noisy instances. In this work, we empirically show that the most popular noise-filtering algorithms have a large False Positive (FP) error rate. In other words, these noise filters mistakenly identify genuine instances as outliers and eliminate them. Th...
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In many practical classification problems, mislabeled data instances (i.e., class noise) exist in the acquired (training) data and often have a detrimental effect on the classification performance. Identifying such noisy instances and removing them from training data can significantly improve the trained classifiers. One such effective noise detector is the so-called ensemble filter, which pred...
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There are two ways to implement frequency domain filtered x LMS (FXLMS) algorithms. The first carries out both control signal generation and control filter updating in the frequency domain, and the second involves implementation of the control filtering in the time domain and updating of the coefficients of the control filters in the frequency domain. Most active noise control literature is foc...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.070548