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finetuned_opt = OptPipe([("first", FooOpt())("second", BarOpt(params))], more_params)
params
BarOpt
more_params
OptPipe
FooOpt
column_transformer = BetterColumnTransformer(
BetterColumnTransformer
[
{"name": "num", "transformer": StandardScaler(), "columns": ["age", "income"]},
StandardScaler
{"name": "cat", "transformer": OneHotEncoder(), "columns": ["gender", "city"]},
OneHotEncoder
]
)
class MyPipeline(Pipeline):
Pipeline
def transform(self, data):
numeric = self.columns(["age", "income"]).apply(StandardScaler())
categorical = self.columns(["gender", "city"]).apply(OneHotEncoder())
combined = self.concat(numeric, categorical)
return combined.then(SVC())
SVC
finetuned_opt = OptPipe(more_params)
finetuned_opt.add_step(RandomOpt(), fraction=0.3)
RandomOpt
finetuned_opt.add_step(fraction=0.4)
finetuned_opt.add_step(fraction=0.3)
finetuned_opt
class OptPipe:
def __init__(self, a, b, c):
self.a = a
self.b = b
self.c = c
def set_params(self):
# einzige Möglichkeit um a b c zu ändern
pass
SimonBlanke /
Hyperactive
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