To view this presentation:

  • If you have an MRS account, click the Login button above.
  • New to MRS?  Create a free account here



  0       0

2014 MRS Spring Meeting


WW5.06 - Machine Learning Applied to Data from Combinatorial Libraries


Apr 23, 2014 4:00pm ‐ Apr 23, 2014 4:15pm

Description

We are actively developing visualization and analysis techniques to rapidly extract trends in composition-structure-property relationships from large data sets from combinatorial libraries. Because data often take on spectral or higher dimensional formats, it is helpful to apply data reduction schemes involving cluster analysis. Examples of techniques we have applied to date include hierarchical clustering using metric multidimensional scaling as the metric, non-negative matrix factorization, and the mean shift theory. They have proven to be extremely useful in deciphering the distribution of structural phases across composition spread samples using diffraction data. We have also applied our techniques to Raman spectra and hysteresis curves. We will also discuss applications of new regression techniques including the relevant vector machines. This work is funded by ONR and DOE.

Speaker(s):

You must be logged in and own this session in order to post comments.

Print Certificate
Review Answers
Print Transcript
Completed on: token-completed_on
Review Answers
Please select the appropriate credit type:
/
test_id: 
credits: 
completed on: 
rendered in: 
* - Indicates answer is required.
token-content

token-speaker-name
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
/
/
token-index
token-content
token-index
token-content