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standard scaler pipeline #26
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looks good, just some small changes to clean up the syntax
few/few.py
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self.ml = ml | ||
self.ml_type = type(self.ml).__name__ | ||
self.ml = Pipeline([('standardScaler',StandardScaler()), ('ml', ml)]) | ||
self.ml_type = type(self.ml.steps[1][1]).__name__ |
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use ml.named_steps['ml']
few/few.py
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@@ -116,11 +117,13 @@ def __init__(self, population_size=50, generations=100, | |||
self.boolean = True | |||
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# instantiate sklearn estimator according to specified machine learner | |||
if self.ml is None: | |||
if self.ml.steps[1][1] is None: |
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see above comment
few/few.py
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@@ -146,7 +149,7 @@ def __init__(self, population_size=50, generations=100, | |||
type(DecisionTreeClassifier()): 'r2', | |||
type(DistanceClassifier()): 'silhouette', | |||
type(KNeighborsClassifier()): 'r2', | |||
}[type(self.ml)] | |||
}[type(self.ml.steps[1][1])] |
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see above comment
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