Search Result "incremental featureselection"


Research Article

Application of Feature Selection Technology Based on Incremental of Diversity in Prediction of Flexible Regions from Protein Sequences

Journal: Letters in Organic Chemistry
Volume: 14 Issue: 9 Year: 2017 Page: 642-647
Author(s): Suqing Yang,Shisai Hu,Ying Zhang,Jun Lv

Prediction of Human Protein Subcellular Locations with Feature Selection and Analysis

Ebook: Frontiers in Protein and Peptide Sciences
Volume: 1 Year: 2014
Author(s): Bi-Qing Li,Tao Huang,Lei Chen,Kai-Yan Feng,Yu-Dong Cai
Doi: 10.2174/9781608058624114010013

Research Article

Prediction of Protein-Peptide Interactions with a Nearest Neighbor Algorithm

Journal: Current Bioinformatics
Volume: 13 Issue: 1 Year: 2018 Page: 14-24
Author(s): Bi-Qing Li,Yu-Hang Zhang,Mei-Ling Jin,Tao Huang,Yu-Dong Cai

Analysis of A Drug Target-based Classification System using Molecular Descriptors

Journal: Combinatorial Chemistry & High Throughput Screening
Volume: 19 Issue: 2 Year: 2016 Page: 129-135
Author(s): Jing Lu,Pin Zhang,Yi Bi,Xiaomin Luo

Research Article

New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes

Journal: Combinatorial Chemistry & High Throughput Screening
Volume: 22 Issue: 10 Year: 2019 Page: 665-674
Author(s): Yan Xu,Yu-Hang Zhang,JiaRui Li,Xiao Y. Pan,Tao Huang,Yu-Dong Cai

Research Article

Radiomic Analysis of Contrast-Enhanced CT Predicts Glypican 3-PositiveHepatocellular Carcinoma

Journal: Current Medical Imaging
Volume: 20 Issue: 1 Year: 2024 Page: 1-10
Author(s):

Systematic Review Article

Machine Learning in Magnetic Resonance Images of Glioblastoma: A Review

Journal: Current Medical Imaging
Volume: 20 Issue: 1 Year: 2024 Page: 1-16
Author(s): Modesto A. Sosa

Bankruptcy Prediction Model Using an Enhanced Boosting Classifier based on Sequential Backward Selector Technique

Ebook: Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
Volume: 3 Year: 2022
Author(s):
Doi: 10.2174/9789815040401122030007

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