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Datascape is a data-mining and modeling tool that is ideal for visualizing and modeling complex multivariate systems and deploying the resulting predictive model efficiently. These Surrogate or Response Surface Models provide insight into the data that you have acquired, putting that data to work for you. Datascape can also be used to replace large data tables and complex calculations in embedded systems to dramatically increase system performance.

Datascape's novel technology has provided valuable solutions where other commercial tools have failed. In many cases, it has demonstrated capabilities surpassing that of neural networks, regression and fuzzy logic systems.


Datascape Simplifies Modeling by Creating a Powerful Tool for Prediction from your Data



Datascape Video
(18 MB Windows Media Player)

Datascape's user interface is easy to use and provides the capabilities that analysts have requested to help accelerate the process of data-mining and modeling. This versatile tool has innumerable time and cost saving applications.  
3D AND 2D VISUALIZATION
Datascape is used to develop accurate, active models from acquired data, enabling new insight into multidimensional data through its powerful visualization options.
EASILY UPDATED
Models are based on a small number of coefficients giving you the power and flexibility to change your project by updating the coefficients rather than replacing the entire embedded model.
UNMATCHED COMPRESSION
Datascape's unique representation yields tremendous data compression opportunities. Huge amounts of data can be represented by a small set of coefficients and a common high performance API.
EASILY DEPLOYED
Once models are created, you can use them to predict outputs based on new inputs. Flexible deployment options are available.
Datascape is a Windows application.
Datascape's technology was a product of research and development conducted by Lockheed Martin over a period of ten years. This technology was licensed to Third Millennium Productions for enhancement and commercialization.

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