Wildlife surveillance using deep learning methods
Sign Up to like & getrecommendations! Published in 2019 at "Ecology and Evolution"
DOI: 10.1002/ece3.5410
Abstract: Abstract Wildlife conservation and the management of human–wildlife conflicts require cost‐effective methods of monitoring wild animal behavior. Still and video camera surveillance can generate enormous quantities of data, which is laborious and expensive to screen… read more here.
Keywords: learning; surveillance using; deep learning; binary classification ... See more keywords
A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification
Sign Up to like & getrecommendations! Published in 2019 at "Metabolomics"
DOI: 10.1007/s11306-019-1612-4
Abstract: Metabolomics is increasingly being used in the clinical setting for disease diagnosis, prognosis and risk prediction. Machine learning algorithms are particularly important in the construction of multivariate metabolite prediction. Historically, partial least squares (PLS) regression… read more here.
Keywords: machine; metabolomics data; machine learning; generalised predictive ... See more keywords
Binary classification of multichannel-EEG records based on the ϵ-complexity of continuous vector functions
Sign Up to like & getrecommendations! Published in 2017 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2017.09.001
Abstract: BACKGROUND AND OBJECTIVE A crucial step in a classification of electroencephalogram (EEG) records is the feature selection. The feature selection problem is difficult because of the complex structure of EEG signals. To classify the EEG… read more here.
Keywords: classification; feature; complexity; eeg records ... See more keywords
Accuracy of regularized D-rule for binary classification
Sign Up to like & getrecommendations! Published in 2018 at "Journal of The Korean Statistical Society"
DOI: 10.1016/j.jkss.2017.11.002
Abstract: Abstract We consider a regularized D-classification rule for high dimensional binary classification, which adapts the linear shrinkage estimator of a covariance matrix as an alternative to the sample covariance matrix in the D-classification rule (D-rule… read more here.
Keywords: classification; accuracy regularized; rule binary; binary classification ... See more keywords
Principal weighted logistic regression for sufficient dimension reduction in binary classification
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the Korean Statistical Society"
DOI: 10.1016/j.jkss.2018.11.001
Abstract: Abstract Sufficient dimension reduction (SDR) is a popular supervised machine learning technique that reduces the predictor dimension and facilitates subsequent data analysis in practice. In this article, we propose principal weighted logistic regression (PWLR), an… read more here.
Keywords: regression; dimension reduction; binary classification; dimension ... See more keywords
Binary classification threatens the validity of cognitive impairment detection.
Sign Up to like & getrecommendations! Published in 2022 at "Neuropsychology"
DOI: 10.1037/neu0000831
Abstract: OBJECTIVE Neuropsychological literature reports varying prevalence of cognitive impairment within patient populations, despite assessment with standardized neuropsychological tests. Within the domain of oncology, the International Cognition and Cancer Task Force (ICCTF) proposed standard cutoff points… read more here.
Keywords: agreement; classification; impairment; binary classification ... See more keywords
A Bayesian Approach to Binary Classification of Mid-Infrared Spectral Data With Noisy Sensors
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2020.2978757
Abstract: The problem of classifying substances using MIR laser and sensors with low signal-to-noise ratio remains challenging. The existing methods rely largely on using lasers at multiple wavelengths and expensive high quality sensors. We propose and… read more here.
Keywords: binary classification; bayesian approach; mid infrared; spectral data ... See more keywords
Machine Learning With the Sugeno Integral: The Case of Binary Classification
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2020.3026144
Abstract: In this article, we elaborate on the use of the Sugeno integral in the context of machine learning. More specifically, we propose a method for binary classification, in which the Sugeno integral is used as… read more here.
Keywords: machine learning; learning sugeno; sugeno integral; binary classification ... See more keywords
K Important Neighbors: A Novel Approach to Binary Classification in High Dimensional Data
Sign Up to like & getrecommendations! Published in 2017 at "BioMed Research International"
DOI: 10.1155/2017/7560807
Abstract: K nearest neighbors (KNN) are known as one of the simplest nonparametric classifiers but in high dimensional setting accuracy of KNN are affected by nuisance features. In this study, we proposed the K important neighbors… read more here.
Keywords: high dimensional; novel approach; important neighbors; approach binary ... See more keywords
Investigation of Involvement between Specific Brain Regions and Evaluation Criteria Elements in a Two-Selections Task
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/3999223
Abstract: It is essential to understand the neural mechanisms underlying human decision-making. Several studies using traditional analysis have attempted to explain the neural mechanisms associated with decision-making based on abstract rewards. However, brain-decoding research that utilizes… read more here.
Keywords: binary classification; brain; decision making; evaluation criteria ... See more keywords
The Contrasting Seasonality Patterns of Some Cancer-Types and Herpes Zoster Can Be Explained by a Binary Classification of Immunological Reactions
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Inflammation Research"
DOI: 10.2147/jir.s392082
Abstract: Abstract A binary classification of the pathogenic immune reactions as anti-inflammatory high-Treg reactions or pro-inflammatory low-Treg reactions explains both the relatively low incidence rate of several types of cancer, and the relatively high incidence rate… read more here.
Keywords: treg condition; binary classification; stage; herpes zoster ... See more keywords