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GitHub / randleon / Decision-Tree-versus-Random-Forest-Performance-on-NY-State-Graduation-Data

Decision trees and random forest models can both be very effective when applied to classification problems. We compared the performance vs. complexity payoff between both models in this example using Pandas and NumPy

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/randleon%2FDecision-Tree-versus-Random-Forest-Performance-on-NY-State-Graduation-Data

Stars: 0
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 5.15 MB
Dependencies parsed at: Pending

Created at: over 1 year ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago

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