Berlin, Germany - KnowledgeMiner Software today is pleased to announce the release of Insights 5.0 for OS X, a major update to its critically acclaimed application that implements original self-organizing modeling for classification, diagnosis, and forecasting problems of complex nature for decision support. Following the principle of Occam’s razor, the app now develops complexity minimized predictive models from observation data, autonomously, and it generates new knowledge in form of explicit model equations that describe the data, mathematically, for further analysis, interpretation, and theory formulation purposes. Insights extracts all information needed for model development from the observation data, exclusively, why it is increasingly recognized as a superior alternative and supplemental tool to established assumption based confirmatory science approaches for complex modeling.

Today, we are facing an ever-widening spectrum of complex problems, which require analysis and research. However, in many cases it is impossible to create reliable analytical models using classical confirmatory science based methods since there is incomplete knowledge of the processes involved, which requires making often unjustified assumptions to fill the missing knowledge. Environmental, medical, and socio-economic problems are but three examples. Here, self-organizing modeling methods help to overcome this knowledge gap and to reveal relevant relationships inherent in complex systems in an adaptive, fast, reliable, and objective way.

Insights for OS X is a professional, yet convenient tool for building predictive models from data of complex systems by model self-organization, autonomously. Taking observational data that describe a system or process, the software constructs a working mathematical model of that system by AI-powered knowledge extraction technologies. It implements a unique set of powerful modeling tools such as self-detection of relevant input factors, cost-optimized and prevalence-sensitive classification, or similar patterns recognition, which is applied to health and life sciences related problems, energy forecasting, sales prediction, financial and resource planning, engineering problems, climate change modeling, and other by many corporations, universities, research institutes, students, and individuals worldwide.

Feature Highlights:

• Original, high-dimensional, self-organizing, inductive knowledge mining from observation data
• Automatically develops analytical models and model ensembles from data along with explicit mathematical equations that describe the data as an interpretation of how the model works
• Integrates all complex tasks, such as relevant variables selection from up to 2000 inputs, knowledge extraction, model development and validation, into one process and hides it from user
• Live Prediction Validation technology
• Model deployment and export to Microsoft Excel, ready-to-use Python, Objective-C, AppleScript source code, or TEXT to be used in Matlab
• Powered by 64-bit, parallel, cross-platform, self-organizing modeling engine for multi-core CPUs

Language Support:

• English, Spanish, and German

System Requirements:

• OS X 10.9 or later
• Any Mac with 64-bit CPU, 8+ GB RAM recommended
• Minimum screen resolution of 1400 x 800 pixel

Pricing and Availability:

Insights for OS X is available as Free, Student, Advanced, or Pro edition exclusively from the KnowledgeMiner Software website. Academic versions can be purchased by contacting KnowledgeMiner Software directly. Review copies are available on request.

Located in Berlin, Germany, KnowledgeMiner Software is a privately held company founded in 1993. The company is active in research, development, consulting, and application of outstanding self-organizing modeling and analysis technologies. It developed the distinguished Insights and Ockham tools for the Mac by implementing a number of original technologies for high-dimensional inductive modeling and global sensitivity analysis. 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, probabilistic energy forecasting, sales and demand predictions, medical diagnosis, and wastewater reuse problems. Copyright (C) 2016 KnowledgeMiner Software. All Rights Reserved. Apple, the Apple logo, iPhone, and iPod are registered trademarks of Apple Inc. in the U.S. and/or other countries.

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