Adaptive Modeler 1.6

Adaptive Modeler by Altreva is a software tool for advanced predictive modeling and forecasting. It uses genetic programming to automatically create mathematical models based on historical data.

Adaptive Modeler can be used for a wide range of applications, including time series forecasting, classification, regression, stock market prediction, demand forecasting, and many others.

Adaptive Modeler uses genetic programming to evolve mathematical expressions that fit the provided data. It starts with a population of randomly generated models and then uses evolutionary algorithms to refine and improve them over multiple generations.

Adaptive Modeler supports both numerical and categorical data. It can handle time series data as well as multidimensional datasets with multiple input variables.

Yes, Adaptive Modeler includes built-in algorithms to handle missing data. It automatically applies appropriate techniques to impute missing values before modeling.

No, Adaptive Modeler provides an intuitive graphical user interface that allows users to build models without any programming knowledge. However, advanced users have the option to extend the functionality using Python scripts.

Adaptive Modeler can create various types of models, including linear regression models, polynomial models, Fourier series models, exponential smoothing models, and many others. Additionally, it can create ensemble models that combine multiple individual models.

Yes, time series forecasting is one of the main applications of Adaptive Modeler. It includes specific features and algorithms designed to handle time-dependent data and capture patterns and trends.

Yes, Adaptive Modeler provides integration capabilities through its Python interface. This allows users to interact with the software programmatically and incorporate it into their existing workflows or applications.

Yes, Altreva offers a free 30-day trial version of Adaptive Modeler. The trial version includes all the features of the full version, allowing users to fully experience the capabilities of the software.