Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30115, first published .
Predicting Writing Styles of Web-Based Materials for Children’s Health Education Using the Selection of Semantic Features: Machine Learning Approach

Predicting Writing Styles of Web-Based Materials for Children’s Health Education Using the Selection of Semantic Features: Machine Learning Approach

Predicting Writing Styles of Web-Based Materials for Children’s Health Education Using the Selection of Semantic Features: Machine Learning Approach

Authors of this article:

Wenxiu Xie1 Author Orcid Image ;   Meng Ji2 Author Orcid Image ;   Yanmeng Liu2 Author Orcid Image ;   Tianyong Hao3 Author Orcid Image ;   Chi-Yin Chow1 Author Orcid Image

Journals

  1. Lee J, Lee S. Identification of Risk Groups for and Factors Affecting Metabolic Syndrome in South Korean Single-Person Households Using Latent Class Analysis and Machine Learning Techniques: Secondary Analysis Study. JMIR Formative Research 2023;7:e42756 View

Conference Proceedings

  1. Rajyalakshmi K, Gunasekaran M. CONTEMPORARY INNOVATIONS IN ENGINEERING AND MANAGEMENT. Comparison of improved support vector machine and multilayer perceptron for the prediction of music genre with improved classification accuracy View