Typeerror Init__ Takes 2 Positional Arguments But 3 Were Given Rfe? The 183 Detailed Answer

Help me please.

The scikit-learn setting does not work data_final_vars=data_final.columns.values.tolist() y=[‘y’] X=[i for i in data_final_vars if i not in y] from sklearn.feature_selection import RFE from sklearn.linear_model import LogisticRegression logreg = LogisticRegression() rfe = RFE(logreg, 20) rfe = rfe.fit(os_data_X, os_data_y.values.ravel()) print(rfe.support_) print(rfe.ranking_) Error in line 7: TypeError: init() took 2 position arguments but 3 was given

TypeError: took 2 position arguments but 3 was given # Python ‘TypeError: took 2 position arguments but 3 were given’ occurred for several reasons: Forget specifies the self argument in a class method.

Forget to define the third argument in the definition of the function.

Passing three arguments to a function takes only two arguments.

Overwrite a built-in function by mistake.

Here’s an example of how the error occurred.

Main.py Copied! class Employee( ) : def increase_salary ( a , b ) : return a + b emp = Employee ( ) result = emp .

increase_salary ( 100 , 100 ) We forget to specify the self-argument in the definition of the class method increase_salary.

Python automatically switches to the class method when it is called, so a method that takes 2 arguments will be passed 3 arguments causing the error.

main.py Copied! class Employee( ) : def increase_salary ( self , a , b ) : return a + b emp = Employee ( ) result = emp .

increase_salary ( 100 , 100 ) in ( result ) itself represents an instance of the class, so when we assign a variable as Specify the self argument in the definition of the method solves the error.

If your method does not use the self argument, you can declare a static method.

chief.py Copied! class Employee( ) : @staticmethod def increase_salary ( a , b ) : return a + b emp = Employee () result = emp .

increase_salary ( 100 , 100 ) in ( result ) A static method does not receive an implicit first argument and can be called on the class or on a version of the class.

The error also occurs when you forget to specify a third argument in the definition of a function or pass 3 arguments to a function that takes only 2.

main.py Copied! def do_math ( a , b ) : returns a + b do_math ( 10 , 20 , 30 ) The do_math function takes two arguments but it is called by 3.

In this situation, we must update the declaration of the function and take the third argument or remove the third argument from the function call.

This is an example of removing an argument from a function call.

chief.py Copied! def do_math ( a , b ) : returns the result a + b = do_math ( 10 , 20 ) in ( result ) And this is an example of specifying the third argument in the definition of the function.

chief.py Copied! def do_math ( a , b , c ): returns the result a + b + c = do_math ( 10 , 20 , 30 ) in ( result ) Make sure that you do not overwrite any function or built-in class by declaring a function with the same name, as that can also cause errors.

I was learning machine learning and got this error.

I think that’s a problem with my local setup.

# Import RFE and LinearRegression from sklearn.feature_selection enter RFE from sklearn.linear_model enter LinearRegression # Run RFE with the number of outputs of the variable equal to 10 lm = LinearRegression () lm.fit (X_train, y_train) rfe = RFE (lm, 10) # run RFE rfe = rfe.fit (X_train, y_train) I get an error after I run the cells on jupyter ————————————————————————— TypeError Traceback (last most recent call) ~AppDataLocalTemp/ipykernel_3420/241754350.py in 3 lm.fit(X_train, y_train) 4 —-> 5 rfe = RFE(lm, 10) # running RFE 6 rfe = rfe.fit(X_train, y_train) TypeError: __init__() takes 2 position arguments but 3 has been given The above code seems to be working for others.

Any help would be appreciated.

Thank.

As you can see in the init method of the RFE class (github.com/scikit-learn/scikit-learn/blob/7e1e6d09b/sklearn/feature_selection/_rfe.py#L176), you can pass only two position arguments (self + estimator).

According to the python documentation (docs.python.org/3.5/reference/compound_stmts.html#function-definitions): The following parameters “*” or “*identifier” are keyword-only parameters and can only be passed used keyword arguments.

In your case, you should type: rfe = RFE (lm, n_features_to_select=10)

my code is giving the error is TypeError: __init__() lost 2 position arguments but 4 were exhibit.

tried to find one more debate but couldn’t get it.

Tried the previously answered questions but didn’t get any proper solution.

My code is as follows: from abc import ABCMeta, abstractmethod class Book(object, metaclass=ABCMeta): def __init__(self,title,author): self.title=title self.author=author @abstractmethod def display(): pass #Write MyBook class class MyBook(Book): def __init__(self, price): self.price = price def display(): print(‘Title: {}’.format(title)) print(‘Author: {}’.format(author)) print(‘Price: {}’.format(price)) title=input() author=input() price=int(input()) new_novel=MyBook(title,author,price) new_novel.display() compiler gives runtime error as following Traceback (last most recent call): File ‘Solution.py’, line 23, in new_novel=MyBook(title,author,price) TypeError: __init__() takes 2 position arguments but 4 have been given Answer Comments inside the code.

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$\begingroup$ I defined a class as below: 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.scaler = StandardScaler(copy, with_mean, with_std) self.column = column self.mean_ = None self.var_ = None def fit(self, X, y = None): 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)] returns pd.concat([X_not_scaled, X_scaled], axis = 1)[init_col_order] When I try to create an object from it: columns_to_scale = [‘col_A’, ‘col_B’] scaler = CustomScaler(columns_to_scale) I got this error: init() took 1 position argument but 4 was given What is the problem? And how to solve it? Environment:

zero Piraeus answer in 2014-05-29 514 In Python, this: my_object.method (‘foo’) …

is the syntactic line, which the interpreter translates behind the scenes into: MyClass.method (my_object, ‘foo’) …

where, as you can see, there are actually two arguments – only the first one is implicit, from the caller’s point of view.

This is because most methods do some work with the object they are called, so there needs to be some way for that object to be referenced to inside the method.

By convention, this first argument is called self inside the method definition: class MyNewClass: def method(self, arg): print(self) print(arg) If you call method(‘foo’) on an instance of MyNewClass, it works as expected: >>> my_new_object = MyNewClass() >>> my_new_object.method(‘foo’) <__main__.MyNewClass object at foo 0x29045d0> Occasionally (but not often), you really don’t care about the object to which your method is bound, and in that case, you can decorate the method with the staticmethod() builtin function to say the following: class MyOtherClass: @staticmethod def method(arg): print(arg)…

in that case, you don’t need to add the self-argument to the method definition, and it still works: