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hyperopt.github.io
What is Hyperopt-sklearn? Finding the right classifier to use for your data can be hard. Once you have chosen a classifier, tuning all of the parameters to get the best results is tedious and time consuming. Even after all of your hard work, you may have chosen the wrong classifier to begin with. Hyperopt-sklearn provides a solution to this problem. Usage from hpsklearn import HyperoptEstimator #
Hyperopt: Distributed Asynchronous Hyper-parameter Optimization Getting started Install hyperopt from PyPI pip install hyperopt to run your first example # define an objective function def objective(args): case, val = args if case == 'case 1': return val else: return val ** 2 # define a search space from hyperopt import hp space = hp.choice('a', [ ('case 1', 1 + hp.lognormal('c1', 0, 1)), ('case 2
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