Insights 4.0: Predictive Models for Web, iOS, and OS X Dev Projects
Berlin, Germany - KnowledgeMiner Software today is pleased to announce the release of Insights 4.0, a major update to its critically acclaimed application that implements outstanding self-learning modeling algorithms to allow users to automatically develop reliable predictive models from data for decision support. With In-Memory database processing and Python and Objective-C source code generation of developed model ensembles for instant implementation into web, iOS, or OS X development projects, Insights 4.0 takes cost and time-to-deploy measures to a new level of applicability and value for academic users and app developers.
Insights for OS X is a professional, yet convenient tool for building predictive models from data of complex systems autonomously. Taking observational data that describes a system or process, the software constructs a working mathematical model of that system by AI-powered, self-organizing 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.
- Original, high-dimensional, self-learning, inductive knowledge mining with ease
- Automatically develops models and model ensembles from data, and it generates the equation that describes the data as a mathematical interpretation of how the model works
- Integrates all complex tasks, such as 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
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 analytical models using classical theoretical systems analysis since there is incomplete knowledge of the processes involved. Environmental, medical and socio-economic systems are but three examples. We are facing complex problems, which do need decision-making, but the means - the models - for understanding, predicting, simulating, and if appropriate controlling such systems are absent. 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 4.0 comes with several example models, such as cost-optimized models for fetal state monitoring, gene expression of tumor tissue, and QSAR models for screening of chemical substances and regulatory purposes. More than 20 examples are included for illustrative purposes, taken from the fields of Climate Change, Energy, Life Sciences, Chemistry, Engineering, and Business.
- English, Spanish, and German
- OS X 10.10 or later
- Any Mac with 64-bit CPU, 8+ GB RAM recommended
- Minimum screen resolution of 1280 x 768 pixel
Pricing and Availability:
Insights for OS X is available as Free, Student, Advanced, or Pro editions exclusively from the KnowledgeMiner Software website. Until November 30, 2015, promotional prices with up to 75% discount are provided. 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 modelling 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 modelling 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 modelling and prediction problems, probabilistic energy forecasting, sales and demand predictions, medical diagnosis, and wastewater reuse problems.
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