We describe the use of a hierarchical clustering algorithm on mass spectra of single particles. In this method, the first cluster is found by searching a data set for the two most similar mass spectra. Then the next most similar spectra or clusters are combined sequentially until a stopping condition is met. Chemically reasonable clusters were obtained for several sets of both laboratory and ambient aerosols. Advantages of this technique include assured convergence without multiple iterations, the ability to handle clusters with widely varying numbers of elements, and good performance even when a continuum of points connects different clusters. A disadvantage of this hierarchical clustering is that it operates on a fixed data set and cannot assign spectra to clusters as the spectra are obtained.
Free access
Cluster Analysis of Data from the Particle Analysis by Laser Mass Spectrometry (PALMS) Instrument
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.