i have an error while running Standard Scaler. it said that it takes 1 positional argument but 4 were given. when i use your guys answers it siad the same. please enligthen me what to do because i cant continue the course.

now i got the answer, its from someone in stackoverflow, here's the code from sklearn.base import BaseEstimator, TransformerMixin from sklearn.preprocessing import StandardScaler 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] i dont know what happens in the code but it works! i can analyze the data further now, hope it will help someone

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Muhammad Aulia

Last answered:

23 Jul 2022

Posted on:

22 Jul 2022

Error in JupyterNotebook with sk learn

in Machine Learning in Python / Course Introduction

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Muhammad Aulia

Posted on:

23 Jul 2022

Error in JupyterNotebook with sk learn

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