The MIMIC Algorithm Implemented in Python
To run the tests just run python -m unittest discover mimicry/test
.
The MIMIC Algorithm Implemented in Python
The MIMIC Algorithm Implemented in Python
To run the tests just run python -m unittest discover mimicry/test
.
I realize that you may not be maintaining this algorithm anymore, but as it is a (if not, the) main alternative to ABAGAIL for ML students, it would be beneficial to take on this capability. Thanks in advance! :)
Changes needed:
Add interations to the init function:
def init(self, domain, fitness_function, samples=1000, iterations=100,
percentile=0.90, typeDomain=None):
Save this and make it available within the function:
self.m = iterations
Adjust the fit() function to iterate:
def fit(self):
"""
Run this to perform m iterations of the Mimic algorithm
:return: A list containing the top percentile of data points
"""
for i in range(self.m):
samples = self.sample_set.get_percentile(self.percentile)
self.distribution = Distribution(samples)
self.sample_set = SampleSet(
self.distribution.generate_samples(self.samples),
self.fitness_function)
return self.sample_set.get_percentile(self.percentile)
mimcry.mimic.Mimic.fit() returning TypeError: fit() takes exactly 1 arguments (2 given) even though only one is given. Please advise.
Occasionally this happens: https://travis-ci.org/mjs2600/mimicry/builds/52506167 We should probably figure out why.
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