Correlation and redundancy on machine learning performance for chemical databases

Author:

Li Hongzhi1,Li Wenze1,Pan Xuefeng1,Huang Jiaqi1,Gao Ting1,Hu LiHong1ORCID,Li Hui1,Lu Yinghua1

Affiliation:

1. School of Information Science and Technology; Northeast Normal University; Changchun 130117 China

Funder

National Natural Science Foundation of China

Science and Technology Development Planning of Jilin Province

Education Department of Jilin Province

Publisher

Wiley

Subject

Applied Mathematics,Analytical Chemistry

Reference39 articles.

1. A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases;Gao;J Chem,2016

2. An accurate and efficient method to predict Y-NO bond homolysis bond dissociation energies;Li;Math Probl Eng,2013

3. Indefinite kernel ridge regression and its application on QSAR modeling;Li;Neurocomputing,2015

4. A novel SVM-kNN-PSO ensemble method for intrusion detection system;Aburomman;Appl Soft Comput,2016

5. A review of ensemble methods in bioinformatics;Yang;Current Bioinformatics,2010

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