Summary of Optimising Random Forest Machine Learning Algorithms For User Vr Experience Prediction Based on Iterative Local Search-sparrow Search Algorithm, by Xirui Tang (1) et al.
Optimising Random Forest Machine Learning Algorithms for User VR Experience Prediction Based on Iterative Local Search-Sparrow Search Algorithm
by Xirui Tang, Feiyang Li, Zinan Cao, Qixuan Yu, Yulu Gong
First submitted to arxiv on: 3 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes an improved method for predicting virtual reality (VR) user experience by combining a sparrow search algorithm with a random forest algorithm. The researchers train and test three models: a traditional random forest model, a model enhanced by the sparrow search algorithm, and a model further improved by an iterative local search-optimised sparrow search algorithm. The results show that the traditional model has poor generalisation accuracy (93% on the training set but only 73.3% on the test set), while the improved models achieve higher accuracy rates: 94% for the model with the sparrow search algorithm and 100% for the model with the iterative local search-sparrow search algorithm. This study provides new ideas and methods for VR user experience prediction, particularly the improved model that can accurately predict and classify users’ VR experiences. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how to make better predictions about people’s experiences in virtual reality. They try out different combinations of algorithms to see which ones work best. The main finding is that a new combination of algorithms does very well – it gets 100% correct on both the training and test sets! This means it can accurately predict what someone will think of their VR experience. This research could help improve VR experiences for people in the future. |
Keywords
» Artificial intelligence » Random forest
