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ACD/Spectrus Workbooks Clustering Add-on

Data Mining with Confidence

Finding similarities or differences between spectra becomes more difficult as the number of spectra increase. Clustering is applied in chemical R&D to group similar formulations in competitive analysis; to evaluate sources of raw materials; and to compare polymorphs and determine good versus bad samples, or real versus counterfeit products.

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ACD/Labs clustering toolset provides scientists with the ability to:

Once groups or classes have been established, new data (samples/spectra) may be compared to existing clusters to determine their proper group. Project knowledge can be further enhanced over time in this ULI-based approach to spectral data analysis.