A Word's Difficulty Level Classification Model Based on Random Forest Algorithm and K-Means Clustering Algorithm
Author:
Affiliation:
1. China Agricultural University,Industrial Design,Beijing,China
2. China Agricultural University,Mechanical and Electronic Engineering,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10154619/10154582/10154713.pdf?arnumber=10154713
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1. DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data[J];grzegorz;BMC Bioinformatics,2022
2. Multi-target assignment hunting strategy of UAV swarm based on improved K-means algorithm and shortest time mechanism[J];bin;Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University,2022
3. A new approach to pollution vulnerability assessment in aquifers using K-means analysis[J];marisela;Environmental Earth Sciences,2022
4. Retraction Note: Complex image recognition algorithm based on immune random forest model[J];xiaoyu;Soft Computing,2022
5. A study on geological structure prediction based on random forest method[J];zhen;Artif Intell Geosci,2022
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