Machine Learning Methods with Noisy, Incomplete or Small Datasets

In many machine learning applications, available datasets are sometimes incomplete, noisy or affected by artifacts. In supervised scenarios, it could happen that label information has low quality, which might include unbalanced training sets, noisy labels and other problems. Moreover, in practice, i...

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Bibliographic Details
Format:	eBook
Language:	English
Published:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:	Information technology industries artificial intelligence Artificial Neural Network auto-encoders binarization COVID19 data augmentation data science deep learning dengue digital-gap Discrete Cosine Transform (DCT) Discrete Fourier Transform (DFT) Discriminant Analysis educational data empirical mode decomposition episodic memory Extreme Learning Machines (ELM) feature elimination feature engineering feature extraction feature importance feature selection few-shot learning functional connectivity functional magnetic resonance imaging gender-gap graph model hierarchical clustering image generation imperfect dataset independent component analysis intelligent decision support Internet of Things (IoT) label correlations machine learning machine translation Markov Chain Monte Carlo (MCMC) multifrequency impedance neural network noise elimination noisy datasets non-negative matrix factorization ontology open contours optimization pairwise evaluation Parkinson's disease permutation-variable importance persistent entropy policy-making support prediction preprocessing recurrent neural network root canal measurement semi-supervised learning shadow detection shadow estimation similarly shaped fish species single sample per person small data-sets small datasets small sample learning smart building social vulnerability sound event detection space consistency sparse representations support-vector machine tensor completion tensor decomposition topological data analysis ultrasound images weighted interpolation map
Online Access:	Open Access: DOAB: description of the publication Open Access: DOAB, download the publication

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Open Access: DOAB: description of the publication
Open Access: DOAB, download the publication

Machine Learning Methods with Noisy, Incomplete or Small Datasets

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