KnowledgeMiner (yX) for Excel 1.2

KnowledgeMiner (yX) for Excel 1.2 is an effective tool which works with data stored in Microsoft Excel for building predictive and descriptive models from this data autonomously and easily.

Major Features:

1. It supports both major releases of Microsoft Excel, 2004 and 2008. The modeling engine of KnowledgeMiner (yX) for Excel implements unique modeling technologies which are built on the principles of self-organization: Learning from noisy data an unknown relationship between output and input of any given system in an evolutionary way from a very simple model to an optimal complex one which generalizes well.
   
2. It is 64-bit parallel software. 64-bit and parallelization allows (yX) to take full advantage of multi-processor and/or multi-core based Macs. It scales to the number of processing elements found at runtime. This means, it runs at optimal speed no matter if the machine it is running on is still a single processor machine or if it is driven by a dual-core or a quad-core CPU or by two quad-core CPUs. This implies that KnowledgeMiner (yX) for Excel will also scale to future many-core hardware not available today. The concluding rule is that (yX) for Excel - unlike the vast majority of any kind of software on the market today - runs faster, almost linear, actually, with increasing number of processing elements and clock speeds
   
3. The new 64-bit parallel modeling engine results in breathtaking performance gains. KnowledgeMiner (yX) for Excel runs more than 600 times faster than the traditional one, according to a recent performance study. This makes KnowledgeMiner users even more productive  and gets complex modeling and prediction tasks done in almost no time.
   
4. These are both based on the same revolutionary data mining algorithms - self-organizing networks of active neurons (gmdh), self-organizing fuzzy rule induction, analog complexing and others that learn and model data.
5. KnowledgeMiner and (yX) can be used for different data mining tasks like classification, modeling, time series forecasting, sequential patterns and clustering.
6. KnowledgeMiner and (yX) are useful and essential for research in all fields of knowledge.

Enhancements:

• [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] Additional plot type for regression models added to display prediction uncertainty in an Excel sheet;
• [new] Automatic generation of graphs for models based on similar patterns including a prediction uncertainty plot;
• [new] A set of example documents on global warming based on current data of land air and sea surface temperatures added;

Requirements:

• Mac OS X 10.5 (Leopard) or newer
• Any multi-core Intel-based Mac to run software concurrently (recommended), PPC Macs to run software sequentially, only
• Microsoft Excel 2004 or 2008