Classifion is a freeware Windows application for chemometrics classification of substances using their mass-spectra. The used multivariate analysis is based on Principal Component Analysis with Mahalanobis Distance (PCA-MD) and it is of one class classifier. Classifion has been tested using mostly mass and optical spectra, but there is no limitation to be used with any other kind of characteristic spectra. The only twist is to find appropriate channel (bin) size, which in case of mass-spec is naturally the mass number.

Where does it sit...
Almost every mass-spectrometry lab is equipped with spectral-library search program with tens of thousands of spectra of pure compounds. The problems begin when you have very complex substances or using mass-spec methods different from those used in the spec-libraries. In some cases you don't need to know what exactly is in the sample, but simply does it belong to a class of samples you already measured. In all these cases you need to use classification software. There are many classification libraries in python or R, but they are general purposed and require certain knowledge of the statistical methods used.
Here Classifion sits, offering you a classification with specialized for mass-spectrometry friendly environment and automation allowing you to classify without interpreting the mass-spectra, so you can concentrate on your immediate work. Some understanding of underlying statistical methods would be beneficial for you, but it is not required.

How does it work...
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 spectra specific information based on statistical  characteristics, not the interpretation of the mass-spectra.  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). Mahalanobis distance will measure a distance between a new (unknown) point and the cluster (the class distribution) in PCA space.

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.

Classifion is one class classifier. Each training correspond to one class and the unknown samples are tested against each training individually. That approach is more convenient - adding new class requires calculating only that class training and better from precision prospective - each training contains and it is optimized for information specific to that particular class. That makes the work with Classifion similar to the spectral-library search software.

Classifion can be controlled remotely from another application (as COM server) combining remote with user access (see Client.zip example project).

What's new in v1.7

  • The optimization procedure has been improved with calculating the classification thresholds based on MDs histogram of the base group and the others against the training.

  • A lot of user interface improvements and some reorganization were implemented.

  • New utilities have been added:

  • Import Data - import external data files with varieties of options (Excel style)

  • Spec-tree Builder - generates a spec-tree/spec-groups files from appropriate folder structure 

  • External Datasets - import a number of datasets from Classifion website