Machine Learning Methods with Noisy, Incomplete or Small Datasets 

<br/><br/><br/>English[eng] 
<br/><br/><label>ISBN: </label>9783040000000 
<br/><br/><label>Subjects--Topical Terms: </label><br/>open contours||similarly shaped fish species||Discrete Cosine Transform (DCT)||Discrete Fourier Transform (DFT)||Extreme Learning Machines (ELM)||feature engineering||small data-sets||optimization||machine learning||preprocessing||image generation||weighted interpolation map||binarization||single sample per person||root canal measurement||multifrequency impedance||data augmentation||neural network||functional magnetic resonance imaging||independent component analysis||deep learning||recurrent neural network||functional connectivity||episodic memory||small sample learning||feature selection||noise elimination||space consistency||label correlations||empirical mode decomposition||sparse representations||tensor decomposition||tensor completion||machine translation||pairwise evaluation||educational data||small datasets||noisy datasets||smart building||Internet of Things (IoT)||Markov Chain Monte Carlo (MCMC)||ontology||graph model||Artificial Neural Network||Discriminant Analysis||dengue||feature extraction||sound event detection||non-negative matrix factorization||ultrasound images||shadow detection||shadow estimation||auto-encoders||semi-supervised learning||prediction||feature importance||feature elimination||hierarchical clustering||Parkinson’s disease||few-shot learning||permutation-variable importance||topological data analysis||persistent entropy||support-vector machine||data science||intelligent decision support||social vulnerability||gender-gap||digital-gap||COVID19||policy-making support||artificial intelligence||imperfect dataset