mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-28 11:17:47 +00:00
Mark Aron Szulyovszky
d3d7184ea4
* feat(Models): added StaticAverageModel for average ensembling * feat(Models): made sure we only pipe in predictions to StaticAverageModel, added StaticNaiveModel as potential baseline * chore(Models): removed unnecessary commented out code
42 lines
850 B
Python
42 lines
850 B
Python
|
|
from typing import Literal, Optional
|
|
from sklearn.base import clone
|
|
from abc import ABC, abstractmethod, abstractproperty
|
|
|
|
class Model(ABC):
|
|
|
|
# data_format: Literal['dataframe', 'numpy']
|
|
data_scaling: Literal["scaled", "unscaled"]
|
|
# data_format: Literal["wide", "narrow"]
|
|
only_column: Optional[str]
|
|
|
|
@abstractmethod
|
|
def fit(self, X, y):
|
|
pass
|
|
|
|
@abstractmethod
|
|
def predict(self, X):
|
|
pass
|
|
|
|
@abstractmethod
|
|
def clone(self):
|
|
pass
|
|
|
|
|
|
class SKLearnModel(Model):
|
|
|
|
# data_format = 'numpy'
|
|
data_scaling = 'scaled'
|
|
only_column = None
|
|
|
|
def __init__(self, model):
|
|
self.model = model
|
|
|
|
def fit(self, X, y):
|
|
self.model.fit(X, y)
|
|
|
|
def predict(self, X):
|
|
return self.model.predict(X)
|
|
|
|
def clone(self):
|
|
return SKLearnModel(clone(self.model)) |