Modeling capabilities have been expanded on our platform. Users can now use the “random forest” method, one of the most popular and effective tools in machine learning for building predictive models.
The random forest method is an ensemble algorithm based on creating multiple decision trees and combining their results to improve the accuracy of forecasts. One of the cases when using this method is especially justified is working with “wide” data tables containing many attributes. In such conditions, one decision tree cannot take into account all available attributes, concentrating only on the most significant of them. However, an ensemble of decision trees is able to take into account the entire available set of attributes, which provides more accurate results.
The addition of the random forest method expands the range of tasks that can be solved using our platform and gives users even more tools to achieve their goals.Try the new functionality right now in your personal account!
