Insights 3.2 for OS X: Automated Forecasting and Workflow Integration

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[] Berlin, Germany - KnowledgeMiner Software today is pleased to announce the release of Insights 3.2, an update to its critically acclaimed application that brings conventional data mining and forecasting to a new level of sophistication and applicability. The software now adds export of ready-to-use predictive models generated in Insights to AppleScript, Excel, and MATLAB, and it implements Auto-updating of models for fast, accurate, and continuous forecasting of market prices, market demand, sales figures, or energy load, for example. Users in nearly any field without being an expert in modeling can build and install powerful predictive models from data, which help to gain new insights into complex phenomena, predict future behavior, simulate "what if" questions, and identify methods of controlling processes. Insights is used for modeling and prediction of engineering problems, climate change, health or life sciences-related questions, or mining collections of data from government agencies.

Feature Highlights:
* High performance self-learning, inductive knowledge mining with ease
* Similar Patterns sequential pattern recognition method with auto-updating for long-term, continuous forecasting
* Model export to Microsoft Excel, to ready-to-use AppleScript code, or to TEXT to be used in MATLAB
* 64-bit parallel software
* Hides all complex processes, such as knowledge extraction, model development, and variables selection, from user
* Self-organizes models and generalizes the equation that describes the data
* Live Prediction Validation technology
* Includes documentation, extra literature, sample data and models for several data samples

Taking observational data that describes a problem, system, or process, Insights constructs a working mathematical model. Compatible with data stored in a variety of popular formats (i.e. Microsoft Excel), Insights has outstanding self-learning, inductive modeling algorithms that allow users to easily extract new and useful knowledge from data to support decision-making. Users can develop predictive models and model ensembles, along with a prediction interval from low to high-dimensional noisy data, of up to several thousands of input variables. Insights creates a validated optimal complex analytical model, automatically, that can be applied and exported to Excel, AppleScript, or MATLAB for further analysis.

Why a self-learning, inductive modeling is needed? Today, there are many problems in practice where it is impossible to create analytical models using classical theoretical systems analysis or common statistical methods since there is incomplete knowledge of the processes involved. A major difficulty in modeling complex systems in such unstructured areas as economics, ecology, sociology, and others is the problem of the researcher introducing his or her own prejudices into the model. Since the system in question may be extremely complex, the basic assumptions of the modeler may be vague guesses at best. It is not surprising that many of the results in these areas are vague, ambiguous, and extremely qualitative in nature. In contrast, inductive models obtained by knowledge mining are derived from real physical data and represent the relationships implicit within the system without or with only little knowledge of the physical processes or mechanisms involved.

Since complex, fuzzy, or very noisy processes are hard to model and predict by known parametric modeling and data mining technologies, Insights features Similar Patterns self-organizing technology. Similar Patterns can be seen as a sequential pattern recognition method that predicts and qualitatively explains fuzzy processes inherently. The method implemented in Insights utilizes an original modeling approach to make it applicable to evolutionary (non-stationary) time processes.

"Insights opens up a wealth of new possibilities to individuals, small business owners and scientists that were previously available only to large entities that could afford expensive data mining application," says Frank Lemke, founder of KnowledgeMiner Software. "The ability to continuously make predictions from auto-associative past patterns is the core of human intelligence. Self-similarity is a phenomenon often found in nature. Our Similar Patterns technology now makes these proven and powerful concepts available for solving forecasting problems in critical fields." There are 3 different editions of Insights with a host of features: Insights Free, Insights Advanced, and Insights Pro. Insights Free is perfect for high model accuracy on smaller identification and classification problems. Insights has been used in a host of solutions and publications including the diagnosis of fetal heart rate signals from a number of measurements, indoor temperature forecasting for energy management and control purposes, global warming and ozone concentration forecasting, and modeling and prediction of energy related problems like crude oil price scenario forecasting and peak oil.

Language Support:
* English, German, and Spanish

Device Requirements:
* OS X 10.7 or later
* Any Mac with 64-bit CPU
* Minimum screen resolution of 1280 x 768 pixel
* For Excel support, Excel versions 2011 or 2008
* 82.8 MB

Pricing and Availability:
Insights 3.2 is available as a free version exclusively from the KnowledgeMiner Software website. Insights 3.2 Advanced and Pro, as well as academic versions, can be purchased by contacting KnowledgeMiner Software directly. Review copies are available on request.

Located in Berlin, Germany, KnowledgeMiner Software was founded in 1993 by Frank Lemke. The company is active in research, development, consulting, and application of self-organizing modeling and knowledge discovery technologies. It developed and implemented a number of original technologies for validation of inductively built data mining models. KMS has been doing consulting in model development and prediction of toxicological and eco-toxicological hazards and risks of chemical compounds from experimental data for regulatory purposes within REACH and participated in three international research projects funded by the European Commission related to QSAR. Other fields of activity have been climate change related modeling and prediction problems, sales and demand predictions, macro- and micro-economic modeling problems like national economy and balance sheet prediction, energy consumption analysis and prediction, medical diagnosis, and wastewater reuse problems. Copyright (C) 2014 KnowledgeMiner Software. All Rights Reserved. Apple, the Apple logo, Mac OS X and Macintosh are registered trademarks of Apple Inc. in the US and/or other countries. Other trademarks and registered trademarks may be the property of their respective owners.


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