Recent advances in decision trees: An updated survey
VG Costa, CE Pedreira - Artificial Intelligence Review, 2023 - Springer
Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …
for their unquestionable utility in a wide range of applications but also for their interpretability …
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
[HTML][HTML] Deep learning and machine vision for food processing: A survey
The quality and safety of food is an important issue to the whole society, since it is at the
basis of human health, social development and stability. Ensuring food quality and safety is …
basis of human health, social development and stability. Ensuring food quality and safety is …
[图书][B] Dynamic mode decomposition: data-driven modeling of complex systems
The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …
Statistical learning with sparsity
T Hastie, R Tibshirani… - Monographs on statistics …, 2015 - api.taylorfrancis.com
In this monograph, we have attempted to summarize the actively developing field of
statistical learning with sparsity. A sparse statistical model is one having only a small …
statistical learning with sparsity. A sparse statistical model is one having only a small …
Robust sparse linear discriminant analysis
Linear discriminant analysis (LDA) is a very popular supervised feature extraction method
and has been extended to different variants. However, classical LDA has the following …
and has been extended to different variants. However, classical LDA has the following …
[PDF][PDF] Do we need hundreds of classifiers to solve real world classification problems?
We evaluate 179 classifiers arising from 17 families (discriminant analysis, Bayesian, neural
networks, support vector machines, decision trees, rule-based classifiers, boosting, bagging …
networks, support vector machines, decision trees, rule-based classifiers, boosting, bagging …
A tutorial review: Metabolomics and partial least squares-discriminant analysis–a marriage of convenience or a shotgun wedding
The predominance of partial least squares-discriminant analysis (PLS-DA) used to analyze
metabolomics datasets (indeed, it is the most well-known tool to perform classification and …
metabolomics datasets (indeed, it is the most well-known tool to perform classification and …
Inferring biological networks by sparse identification of nonlinear dynamics
Inferring the structure and dynamics of network models is critical to understanding the
functionality and control of complex systems, such as metabolic and regulatory biological …
functionality and control of complex systems, such as metabolic and regulatory biological …
Real-time movie-induced discrete emotion recognition from EEG signals
Recognition of a human's continuous emotional states in real time plays an important role in
machine emotional intelligence and human-machine interaction. Existing real-time emotion …
machine emotional intelligence and human-machine interaction. Existing real-time emotion …