Classifion is chemometrics software for classification of substances using their mass-spectra. The used discriminant analysis is based on Principal Component Analysis with Mahalanobis Distance (PCA-MD) - part of multivariate analysis. Classifion has been tested using mass-spectra, but there is no limitation to be used with any other kind of characteristic spectra (e.g. VIS, IR, NMR). In latter case the x-values of the spec must be the detector channel number.
Classifion needs to be "trained" using several measured spectra per substance. The "training" itself could be conducted automatically or manually (supervised). The aim of the training is to extract substance specific information based on statistical characteristics, but not on the interpretation of the mass-spectra. Having some knowledge on the mass-spectra structure could improve classification precision. Mathematically speaking the extraction is down to reducing the dimensionality of the spectra variable space (to each mass corresponds one dimension). PCA is well-known such technique, which offers other advantages as ordering the principal component by "significance" (useful for noise reduction).
Classifion can train itself entirely on autopilot. Just import your data, run Autopilot, sit back and enjoy the view. The results will show you how successful the training was, so in case of problem you should re-examine your data or do supervised training.
The feature which makes Classifion better than the most of PCA software out there, is the use of proper factor space for each substance separately, instead of traditional approach of using common factor space for all substances. That improves the classification precision and makes the work with Classifion similar to the spectral-library search software.
Requirements: R project software
What's New: new release
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