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Classification random forest with exact conditioning for spatial prediction of categorical variables被引量：1
《Artificial Intelligence in Geosciences》2021年第1期82-95,共14页Francky Fouedjio 
Machine learning methods are increasingly used for spatially predicting a categorical target variable when spatially exhaustive predictor variables are available within the study region.Even though these methods exhib...
关键词：Categorical variable CLASSIFICATION Exact conditioning Principal component analysis Signed distance Spatial prediction Quadratic programming 
Classification of Fundus Images Based on Deep Learning for Detecting Eye Diseases被引量：4
《Computers, Materials & Continua》2021年第4期411-426,共16页Nakhim Chea Yunyoung Nam 
supported by the KIAT(Korea Institute for Advancement of Technology)grant funded by the Korea Government(MOTIE:Ministry of Trade Industry and Energy)(No.P0012724);the Soonchunhyang University Research Fund.
Various techniques to diagnose eye diseases such as diabetic retinopathy(DR),glaucoma(GLC),and age-related macular degeneration(AMD),are possible through deep learning algorithms.A few recent studies have examined a c...
关键词：Multi-categorical classification deep neural networks GLAUCOMA age-related macular degeneration diabetic retinopathy 
Combined Use of k-Mer Numerical Features and Position-Specific Categorical Features in Fixed-Length DNA Sequence Classification
《Journal of Biomedical Science and Engineering》2017年第8期390-401,共12页Dau Phan Ngoc Giang Nguyen Favorisen Rosyking Lumbanraja Mohammad Reza Faisal Bahriddin Abapihi Bedy Purnama Mera Kartika Delimayanti Mamoru Kubo Kenji Satou 
To classify DNA sequences, k-mer frequency is widely used since it can convert variable-length sequences into fixed-length and numerical feature vectors. However, in case of fixed-length DNA sequence classification, s...
关键词：Sequence CLASSIFICATION NUMERICAL and CATEGORICAL FEATURES Feature Selection 
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