Insights is original 64-bit parallel software for building predictive models from data, automatically, by evolutionary, self-organizing modelling approaches. Taking observational data that describes a problem, system, or process, the software constructs a working mathematical model. Compatible with data stored in a variety of popular formats (e.g., Microsoft Excel), its AI-powered, self-organizing, modeling algorithms allow users to easily extract new and useful knowledge to support decision-making.
Whether applied to sales prediction, financial and resource planning, engineering problems, climate change, health or life sciences related questions, or mining collections of data from government agencies, KnowledgeMiner 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 applications. Users in nearly any field can employ the easy-to-use software to analyze noisy data sets and build powerful models, which can be used to help to gain new insights into complex phenomena, predict future behavior, simulate “what-if” questions, and identify methods of controlling processes.
Feature Highlights
- Brings high-performance Personal Knowledge Mining to users with unprecedented ease of model building and deployment – takes full advantage of the computing power of your Mac;
- Hides all complex processes of knowledge extraction, model development, dimension reduction, variables selection, noise filtering, and model validation from the user;
- Self-organizes linear or nonlinear, static or dynamic regression models and model ensembles – generates the equation that describes the data;
- Checks if, and the extent to which, the developed model reflects a valid relationship or if it just models noise – employs advanced validation methods based on higher-dimensional modeling;
- Live Prediction Validation technology – for the first time, gives direct information about model stability for the given input values;
- Generated analytical models can be used for Status Quo or What-If prediction, analysis, simulation, or optimization problems;
- Optionally, it implements models and model ensembles in Excel – model export requires Microsoft Excel for Mac 2011 or 2008.
What's New
Version 4.0:Note: Now requires OS X 10.10 or later.
- Significantly improved processing speed by new in-memory database; option between fast in-memory DB or file-based DB for large numbers of data records.
- New model export to Python and Objective-C. Integrate ready-to-use source code of your developed models into your web applications or other projects. Works on both individual models and model ensembles.
- Display of model accuracy of predictions in model plots on-the-fly as an immediate measure of model performance on new data.
- For classification models, additional display of key discrimination parameters in scatter plot for easy evaluation of the power of the model on predicted data.
- Updated and new examples added:
- Gene expression of 2000 genes (inputs) for modeling tumor tissue as an example for under-determined, high-dimensional modeling;
- Network intrusion detection as an example for the problem of detecting rare events;
- Ionosphere modification and analysis of pulsed high-power radar signals from a phased array of antennas;
- Daily ozone level detection.
- General maintenance and bug fixing.
Requirements
OS X 10.10 or later, 64-bit processor
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Size: 93.6 MB
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