Self-organizing, Parallel, High-Dimensional Modeling now for Excel 2011!

November 21, 2011: New Features of KnowledgeMiner (yX) for Excel version 2.9.1

• [New] Improved Charting. Now displays actual vs. predicted data on both predicted and learning data.
• [update] Tutorial updated.

New Features of KnowledgeMiner (yX) for Excel version 2.9

• [update] General maintenance and performance improvement of the software.
• [update] New example document "What Drives Global Warming?" added with models and data referencing to a recent post at our Global Warming Prediction Project site.

New Features of KnowledgeMiner (yX) for Excel version 2.7

• [new] Now all editions support multiple cores/CPUs resulting in considerable performance improvements (almost proportionally with the number of cores/CPUs);
• [new] Improved binary classification modeling and plots;
• [new] Enhancements for predicting dynamic models;
• [update] Renaming editions: Now Silver and Gold for formerly Basic and MultiCore editions.

New Features of KnowledgeMiner (yX) for Excel version 2.6.1

• [new] Supports Excel for Mac 2011;
• [new] Faster import of data for modeling from Excel;
• [bug] Fixes a problem when exporting a model with submodels of more than 255 characters to Excel;
• [update] Simulation for crude oil price development for the coming 15 years from projections of world oil consumption and remaining oil reserves;

New Features of recent versions of KnowledgeMiner (yX)

• [new] Inputs range check implemented for models exported to Excel;
• [new] First version with two editions: Basic edition for entry-level modeling and data mining needs, and MultiCore edition for high-end, high-performance parallel forecasting, modeling, and classification purposes;
• [bug] Fixes a bug that in rare situations may cause the program to crash when running Similar Pattern search;
• [new] A number of new examples & models added:
  • 18 Global Warming Prediction models;
  • Sun activity prediction for cycles 24 and 25;
  • World primary energy consumption prediction till 2020;
  • World oil reserves and oil price simulation and prediction till 2025;
  • CO2 emission from energy consumption by fuel prediction till 2025;
  • SF Solar Energy Incentive Program;
  • Developmental Toxicity of 292 chemical compounds QSAR model;
  • Multi-processor, multi-user computer system activity prediction;

New Features of KnowledgeMiner (yX) for Excel versions 2.0 - 2.2

• [new] Introduction of a targeted modeling purpose as part of the setup process: Prediction in time, static modeling, binary classification;
• [new] For static and binary classification models three different Active Neuron types are available now: Polynomial, Radial Basis Function, and Sigmoidal function. Full support for all three types including exporting models to Excel;
• [new] Improved prediction accuracy when using Similar Patterns modeling technology;
• [new] For regression models, model export to Excel improved;
• [new] Prediction project added which models and predicts global land air and sea surface temperatures for 9 global areas 36 months ahead. This is an open project which will be updated regularly!
• [new] High-dimensional modeling which scales to data sets of very small (< 20) to large number of samples (<= 1M) and from small to large number of potential inputs (<= 50,000). Not any prior variables selection is necessary!
• [new] Original tools to noise immunity and evaluation of models derived from data to improve reliability of models and to minimize the risk of getting invalid or chance models from badly sized data sets. More ...
• [new] 64-bit parallel software. Ultra-fast processing of very computation intensive algorithms by 64-bit, multi-core/multi-processor, and vector processing support. The software automatically scales to the number of CPU-cores found at runtime to take full advantage of current and future multi-core hardware. The basic rule: Modeling speed grows with every core and/or processor available at runtime. More ...
• [new] Climate change modeling and prediction project added. This project is possible now since it requires building reliable models from data sets which are high-dimensional in input variables space;
• [updated] Tutorial and documentation;

Features of past (yX) for Excel versions

• [new] Improved model selection procedure during model self-organization which may lead to more accurate models;
• [new] Automatic generation of per-sample model and prediction uncertainty now also for self-organized regression models;
• [new] Automatic generation of graphs for models in Excel including a prediction uncertainty plot;
• [new] Significant performance improvement for building regression models on data sets with large number of samples;
• [new] Essential memory requirement reduction for self-organizing regression modeling;