Interrelation Mining for Biomarkers and Target Groups

If you do not draw the right conclusions from your data then you miss big opportunities or face large risks. To evaluate your data you may have tried several mathematical approaches, different software systems, and support by educated math people. But still the results remain vague or complicated and you are uncertain about the quality of your results and have not understood how to improve them.

Interrelation Mining evaluates in a way so that you understand your data and know the conclusions. The results are provided within shortest time, because no neural network generation or similar efforts are necessary.

Interrelation Mining shows which are the most decisive parameters and most typical samples for your purpose:

- It improves your predictive analytics by up to 20%

- It leads you to the largest and most relevant segment of your samples

- It shows you the most typical customers buying your product

- It makes your data sampling more effective

- It helps you to match the needs of your target group

But be aware: Interrelation Mining may also reveal that your data contains little or no information! Long term observation has shown: Once Interrelation Mining has not found significant information in your data, then no other approaches are found, that reveal significant information.

Interrelation Mining uses a special fuzzy approach. It is a general procedure and successful in many applications for the identification of biomarkers for severe diseases and for the determination of target groups of customers. It is also appropriate for some (biometric) sensors. Customers appreciate the useful, reliable, and comprehensible results.

Contact Systaim, understand your data, and innovate successfully!

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