Using machine learning algorithms to solve data classification problems using multi-attribute dataset

Abstract

This paper discusses various machine learning techniques such as decision trees, Kohonen maps neural network method, and correlation analysis. The training of neural networks and further comparative analysis was carried out using a real estate price segment classification dataset. The overall quality of the data collected in the dataset was evaluated using the correlation analysis method, while the other methods were used to predict the target variable. The obtained data were summarized in a comparative table. As a result of the work done, a relatively high accuracy was obtained using a large number of parameters in the work of almost all methods, the only exception is the neural network method, which does not work very correctly in the selected software product