Work

Study on the models of machine learning for better classification

Year: 2024

Type: conference-paper

Abstract: Up to now, with the development of artificial intelligence, artificial energy technology has been widely used in medicine, text recognition, intelligent speech and other fields. As an important branch of artificial intelligence, machine learning plays a pivotal role in accumulating knowledge for artificial intelligence. In order to study better machine learning methods, this paper compares three machine learning models, Gaussian mixture model (GMM), random forest (RF) and hidden Markov model (HMM), analyzes and compares their advantages and disadvantages and better application fields in terms of accuracy and complexity, and combines simple algorithms to explore a model with higher accuracy. Experimental results have validated the model

DOI: 10.1145/3718391.3727887

Authors: Yangfan Cui, Guangsong Yang, Yuanfa Liu, Guowei Lei, Wenqing Ni

Institution: Jimei University

Language: English

Topic: Data Mining and Machine Learning Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: National Science Foundation, Natural Science Foundation of Fujian Province, Jimei University

Award: G3969208429

OpenAlex ID: W4411747216

FWCI:

Cites: 7

Cited by:

Related to: 10