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pythonmachine-learningscikit-learnpreprocessorattributeerror
QHarr
QHarr

Reputation: 84455

How to use different preprocessing functions in python3 using a for loop?

I am currently looking at scikit learn's preprocessing functions.

I wanted to know if i can loop over a pre-defined list of pre-processing functions such that i don't have to write out in full the set up code for each function.

E.g. code for one function:

T = preprocessing.MinMaxScaler()
X_train = T.fit_transform(X_train) 
X_test = T.transform(X_test)

My attempt to loop over a pre-defined list so as to use different pre-processing functions:

pre_proc = ['Normalizer','MaxAbsScaler','MinMaxScaler','KernelCenterer', 'StandardScaler']

     for proc in pre_proc:
         T = 'preprocessing.'+ proc +'()'
         X_train = T.fit_transform(X_train)
         X_test = T.transform(X_test)

Currently this is yielding the following which is not surprising:

-->   37    X_train = T.fit_transform(X_train)

      38    X_test = T.transform(X_test) 

      39     for i in np.arange(startpt_c,endpt_c, step_c):

      AttributeError: 'str' object has no attribute 'fit_transform'

I think i need to have the string as the correct object type to then call the method on i.e. have it recognised as a function.

Is there a way i can do this that satisfies my objective of using a loop?

Setup: Windows 8, 64 bit machine running Python 3 via Jupyter notebook in Azure ML studio.

Upvotes: 0

Views: 923

Answers (1)

Clock Slave
Clock Slave

Reputation: 7957

The problem lies in this line of your code

pre_proc = ['Normalizer','MaxAbsScaler','MinMaxScaler','KernelCenterer', ...

What you are doing here is creating a list pre_proc that is basically just a list of strings. Python has no idea that you actually meant them to be functions. And so when you try to use T = 'preprocessing.'+ proc +'()' , python throws an error and say, that T is a string and has not method such as fit_transform. So instead of using strings, use the actual function names, i.e., don't put them in quotes. Use them like so - 

pre_proc = [preprocessing.Normalizer, preprocessing.MaxAbsScalar, preprocessing.MinMaxScalar, preprocessing.KernelCenterer, preprocessing.StandardScaler]

Upvotes: 2

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