NEW YORK, N.Y. — The Monument team is pleased to announce the addition of classification and regression methods into our zero-code machine intelligence platform. Users can now estimate any types of classes or levels for your data. Monument will automatically adjust to your data set.
These classification and regression algorithms open up entirely new use cases across a variety of industries, such as fraud detection, value appraisal, customer categorization, and machine failure.
The classification algorithms are Support Vector Machine (SVM), Light Gradient Boosted Machine (LightGBM), and Logistic Regression (LogReg). These features expand on Monument’s robust suite of time-series algorithms.
Classification algorithms enable users to use training datasets to build algorithms that can infer characteristics about new data. Typical use cases include:
- Fraud detection — determine whether a pending bank transaction is fraudulent,
- Inference of demographic characteristics — determine the typical age range for people living in a certain area, and
- Merchandising strategy analysis — determine whether a given customer is a likely purchaser of a specific product.
The latest edition of Monument also adds several new capabilities to our suite of time-series algorithms, including feature importance. With feature importance, you can quickly identify which features are most meaningful for your predictions.
These features represent a major milestone in Monument’s development and promise to unlock significant value for users across industries.
Visit www.monument.ai for more information.