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Machine Learning: Final Presentation James Dalphond James McCauley Andrew Wilkinson Phil Kovac Data Set: Yeast GOLD TEAM.

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Presentation on theme: "Machine Learning: Final Presentation James Dalphond James McCauley Andrew Wilkinson Phil Kovac Data Set: Yeast GOLD TEAM."— Presentation transcript:

1 Machine Learning: Final Presentation James Dalphond James McCauley Andrew Wilkinson Phil Kovac Data Set: Yeast GOLD TEAM

2 WEEK 4 GOALS Combined our four datasets  Run the fast random forests algorithm. Run our data sets against other species  Arabidopsis.  Herpes. NOTE: For interspecies runs and same species, we applied the “Leave One Out” method as well as the full combined sets.

3 Best Performance All Sets 86.19%500 Trees and 29 Features Worst Performance No Local 85.21%1000 Trees and 117 Features Same Organism Testing

4 Yeast vs. Arabidopsis Best Performance No Primary65.04%500 Trees and 7 Features Worst Performance No Physiochemical56.61%500 Trees and 21 Features

5 All Arabidopsis Runs (Train on Yeast)‏

6 Yeast vs. Herpes Best Performance No Primary51.170%500 Trees and 27 Features Worst Performance No Local48.830%500 Trees and 26 Features

7 All Herpes Runs (Train on Yeast)‏

8 Herpes vs. Arabidopsis (Train on Yeast)


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