DBC-Forest: Deep forest with binning confidence screening
Sign Up to like & getrecommendations! Published in 2022 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.12.075
Abstract: As a deep learning model, deep confidence screening forest (gcForestcs) has achieved great success in various applications. Compared with the traditional deep forest approach, gcForestcs effectively reduces the high time cost by passing some instances… read more here.
Keywords: confidence; binning confidence; dbc forest; confidence screening ... See more keywords
Identifying Antitubercular Peptides via Deep Forest Architecture with Effective Feature Representation.
Sign Up to like & getrecommendations! Published in 2024 at "Analytical chemistry"
DOI: 10.1021/acs.analchem.3c04196
Abstract: Tuberculosis (TB) is a severe disease caused by Mycobacterium tuberculosis that poses a significant threat to human health. The emergence of drug-resistant strains has made the global fight against TB even more challenging. Antituberculosis peptides… read more here.
Keywords: antitubercular peptides; deep forest; framework; peptides via ... See more keywords
Deep forest model for diagnosing COVID-19 from routine blood tests
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-95957-w
Abstract: The Coronavirus Disease 2019 (COVID-19) global pandemic has threatened the lives of people worldwide and posed considerable challenges. Early and accurate screening of infected people is vital for combating the disease. To help with the… read more here.
Keywords: deep forest; covid routine; forest model; model ... See more keywords
Identification of miRNA-disease associations via deep forest ensemble learning based on autoencoder
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac104
Abstract: Increasing evidences show that the occurrence of human complex diseases is closely related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease-related miRNAs is essential for the diagnosis and treatment of complex human… read more here.
Keywords: via deep; disease; deep forest; disease associations ... See more keywords
MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework
Sign Up to like & getrecommendations! Published in 2024 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbae530
Abstract: Abstract The gut microbiota plays a vital role in human health, and significant effort has been made to predict human phenotypes, especially diseases, with the microbiota as a promising indicator or predictor with machine learning… read more here.
Keywords: predicting host; host; phenotypes metagenomic; host phenotypes ... See more keywords
Network-based prediction of drug-target interactions using an arbitrary-order proximity embedded deep forest
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa010
Abstract: MOTIVATION Systematic identification of molecular targets among known drugs plays an essential role in drug repurposing and understanding of their unexpected side effects. Computational approaches for prediction of drug-target interactions (DTIs) are highly desired in… read more here.
Keywords: network based; network; deep forest; drug ... See more keywords
Imprecise Deep Forest for Partial Label Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3042838
Abstract: In partial label (PL) learning, each instance corresponds to a set of candidate labels, among which only one is valid. The objective of PL learning is to obtain a multi-class classifier from the training instances.… read more here.
Keywords: label; training; deep forest; ecoc algorithm ... See more keywords
An Effective Tumor Classification With Deep Forest and Self-Training
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3096241
Abstract: In recent years, tumor classification based on the gene expression omnibus has become a continuous attention field in the area of bioinformatics. Integration machine learning techniques are an efficient methods to solve these problems. Generally,… read more here.
Keywords: tumor classification; unlabelled samples; deep forest; self training ... See more keywords
Internet Financial Credit Scoring Models Based on Deep Forest and Resampling Methods
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3239889
Abstract: In recent years, deep learning credit scoring models have become a hot research topic in Internet finance. However, most of the existing studies are based on deep neural network models, whose structure is difficult to… read more here.
Keywords: credit; credit scoring; resampling methods; deep forest ... See more keywords
Estimation of Vegetation Indices With Random Kernel Forests
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3261129
Abstract: Vegetation indexes help perform precision farming because they provide useful information regarding moisture, nutrient content, and crop health. Primary sources of those indexes are satellites and unmanned aerial vehicles equipped with expensive multispectral sensors. Reducing… read more here.
Keywords: vegetation; deep forest; non linear; deep forests ... See more keywords
Remote Sensing Image Change Detection Based on General Deep Forest Module
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3415054
Abstract: Remote sensing image change detection, as one of the important branches of remote sensing technology, has been greatly developed and improved in recent years. The effectiveness of change detection is unstable, as deep learning components… read more here.
Keywords: detection; change detection; remote sensing; sensing image ... See more keywords