Performance Analysis of Machine Learning Techniques, Pattern Detection and Model Optimisation
摘要
This paper focuses on the application of three data analysis techniques – decision trees, neural networks and self-organising Kohonen maps – to identify internal dependencies in a wide range of data. Based on the analysis of a dataset including patient information, the performance of these methods in classification and prediction is compared. The results emphasise the importance of method selection depending on the characteristics of the data and provide a basis for further research in the application of machine learning in various fields.