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Investigator ML Software for Pattern Recognition

Posted: June 11th, 2020, 12:20 pm
by sreichenbach
This past academic year, GC Image™ sponsored a student-group project to further develop Investigator ML™, a program in the GC Image software suite for multidimensional chromatography that uses machine learning (ML) to perform pattern recognition tasks such as classification, identification, regression, and other tasks. A team of six upper-division undergraduate students in the Computer Science and Engineering (CSE) Department at the University of Nebraska – Lincoln (UNL) undertook the project to extend the software’s pattern recognition capabilities from binary-class problems to multi-class problems, to add several additional pattern recognition algorithms, and to improve the software architecture and testing infrastructure. The year was especially challenging because all of their work after mid-March was done remotely, but the team did a great job and were quite successful.

Here are links to a project summary and video produced by the students:
https://cse.unl.edu/senior-design/showcase-projects


Based on that work, GC Image plans to soon release a new version of Investigator ML software to support multi-class pattern recognition from chromatographic analyses of complex sample sets. The new version:
  • Extends pattern recognition from binary-class problems to multi-class problems.
  • Implements additional ML methods.
  • Supports additional methods for data normalization, test-set generation, and cross-validation.
  • Provides additional performance metrics and new visualization tools.
Image

In addition to the ML methods in the current software — linear discriminant analysis (LDA) and k-nearest neighbors (KNN), the new version supports quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA), and linear regression (LR). All of the ML methods can be applied to multi-class data sets with additional performance metrics and multi-class visualizations. Data sets can be optionally normalized by mean, range, or standard distributions; test sets can be generated randomly; and cross-validation can be performed with either leave-p-out or k-fold regimes.

If you are interested in serving as a beta-tester for the upcoming new version of GC Image Investigator ML, please send email to info@gcimage.com.

Re: Investigator ML Software for Pattern Recognition

Posted: August 20th, 2020, 10:30 am
by qtao
We are pleased to provide early access to Investigator ML v1.1.0 Beta for public testing. This beta release includes new features and improvements mentioned above. The new features are considered stable but may have known problems that will be fixed in the final release.

The plugin requires GC Image or LC Image v2.9 (64 bit) or later.
  1. Download here: the Investigator ML plugin
  2. Double click to run the installer exe.
  3. Extract it to the GC Image or LC Image installation folder as shown below.
Image