Resolved: creating custom CustomScalar
when i excute thi line code absentism_scaler.fit(unscaled_input)
it give me error
AttributeError: 'CustomScaler' object has no attribute 'copy'
Hi Mostafa!
Thanks for reaching out.
This error stems from the code you've executed previously in your *.ipynb file. We are aware that this may mean that you have made one of potentially a number of errors, but it is not exactly so. From the screenshot you've shared, it seems that you may have not created the unscaled_inputs in the way shown in the course. Therefore, can you please revise/restart the kernel and re-run all cells in the suggested order, to ensure that this variable contains the relevant content?
Looking forward to your answer.Best,
Tsvetelin
I have encounter same issue.
i have followed exactly the same, and also _ _ init _ _ using
self.scaler = StandardScaler(copy=copy, with_mean=with_mean, with_std=with_std)
maybe due to this FutureWarning?
try this
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class CustomScaler(BaseEstimator, TransformerMixin):
def __init__(self, columns, copy=True, with_mean=True, with_std=True):
self.columns = columns
self.copy = copy
self.with_mean = with_mean
self.with_std = with_std
def fit(self, X, y=None):
self.scaler = StandardScaler(copy= self.copy, with_mean=self.with_mean, with_std=self.with_std)
self.scaler.fit(X[self.columns], y)
self.mean_ = np.mean(X[self.columns])
self.var_ = np.var(X[self.columns])
return self
def transform(self, X, y=None, copy=None):
init_col_order = X.columns
X_scaled = pd.DataFrame(self.scaler.transform(X[self.columns]), columns=self.columns)
X_not_scaled = X.loc[:, ~X.columns.isin(self.columns)]
return pd.concat([X_not_scaled, X_scaled], axis=1)[init_col_order]
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i modified the code from the video using this solution on stack overflow, and it worked.
https://stackoverflow.com/questions/70587280/sklearn-attributeerror-customscaler-object-has-no-attribute-copy
