January 2020
Intermediate to advanced
346 pages
9h 8m
English
Content preview from Hands-On Genetic Algorithms with Python
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Running the conventional grid search
The conventional, exhaustive grid search, covering all 200 possible combinations, needs to be run next. The search results indicate that the best combination was n_estimators = 70, learning_rate ≈ 0.359, and algorithm = 'SAMME.R'.
The classification accuracy that we achieved with these values is about 93%, which is a vast improvement over the original 65%. The search runtime was about 32 seconds:
performing grid search...best parameters: {'algorithm': 'SAMME.R', 'learning_rate': 0.3593813663804626, 'n_estimators': 70}best score: 0.9325842696629213Time Elapsed = 32.180874824523926
Next comes the genetic-powered grid search. Will it match these results? Let's find out.
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