A powerful decision-tree approach to multivariate modeling of complex dataRequest a demo Request a quote brochure
Improve modeling of complex data with powerful Hierarchical Modeling software. Our new software uses a powerful decision-tree approach which makes modeling of non-linear data more efficient and robust, by allowing Classification and Prediction models to be joined in a multi-level structure.
We have two new tools available:
This software is a plug-in to The Unscrambler® X software. It is used to develop hierarchical models and can be used for off-line data analysis.
This software is designed for end-users to apply hierarchical models in real-time by integrating them into spectrometers or CAMO´s Process Pulse software.
The latest version of this powerful classification engine includes enhanced features, even greater ease of use and powerful classification models.
When analyzing process or other complex data, it can be difficult to make a global prediction or classification model that predicts well in every area. Therefore, it is often necessary to refine models based on the output of initial investigations, which is usually done manually and in many steps, becoming a laborious and time-consuming process which is prone to error.
Hierarchical models join a number of multivariate models using logic statements in order to arrive at a single, unique result. This is the classic logic tree or decision tree approach, where the analysis in one step is guided by the previous step.
Hierarchical models are ideal for applications such as:
The software is designed for R&D, Production, Engineering and QA/QC environments where there is a need for developing and implementing run-time control models for process monitoring applications. It is suitable for use by Production supervisors, Quality Assurance teams, Technical Services and control system designers.
Hierarchical models allow a number of multivariate models to be joined using logic statements in order to arrive at a single, unique result. Most of the powerful classification, prediction or projection methods in The Unscrambler® X can be used as the building blocks.