Python Framework that compares 7 different Machine Learning algorithms' accuracy, precision, and F-Beta scores efficiently (~0.15 second runtime) for a given user's training and testing data, and returns the highest scoring of each, along with automated hyperparameter optimization.
pip install Modelrithm
- sklearn
- matplotlib
- numpy
from Modelrithm import Modelrithm
model = Modelrithm(X_test, Y_train, X_test, Y_train)
model.Classification()
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Aided in increasing accuracy, precision, and f-beta score of a classification problem using satellite pictures of the earth and moon.
- This application is included under the 'Examples' folder
Winner, Lockheed Martin Aerospace Challenge - SBHacks 2017
- Hyperparameter optimization by Random Search (not Grid Search, takes too long).