Minitab helps companies and institutions to identify trends, solve problems and discover valuable insights in data by delivering a comprehensive and best-in-class suite of data analysis and process improvement tools. By making advanced machine learning easy-to-use and understand, companies around the globe can access the power of these methods to solve complex problems and predict outcomes better, faster and easier than ever before.”
Slovin, President and Chief Executive Officer of Minitab, said: “Minitab’s predictive analytics module underscores our commitment to helping organizations accelerate their transformations. Now, Minitab is making these methods accessible to everyone, not just data scientists, no matter where they are on their analytics journey.
Developed by the inventors of tree-based modeling techniques, Minitab is the only company in the world to offer these branded and popular methods. Minitab’s predictive analytics module consists of proprietary methods such as Classification and Regression Trees (CART®), the original Random Forests®, a classification algorithm consisting of many decision trees and TreeNet®, Minitab’s own gradient boosting methodology. Skillfully predict, compare alternatives and forecast with ease using Minitab’s revolutionary predictive analytics techniques. With Minitab’s new predictive analytics module, users will be able to solve more challenging problems, tap into deeper insights and visualize complex interactions in a better, faster, easier, and more accurate way. In addition to Minitab’s classical methods, users can now leverage the power of advanced machine learning methods through clicks - by deploying Minitab’s new predictive analytics module – or code, by integrating with open-source languages R or Python. State College, Ap(GLOBE NEWSWIRE) - Minitab, LLC, the market leader in data analysis, predictive analytics and process improvement, announced the launch of new predictive analytics capabilities and advanced machine learning methods in Minitab® Statistical Software.
0 kommentar(er)
