MyFancyClassifier Class Reference

Public Member Functions
	__init__ (self, *my_fancy_parameters)
	fit (self, X, y)
	predict (self, X)

Detailed Description

 Let's assume we have written our own classifier (or installed something from github) 

Definition at line 21 of file how_to_use_arbitrary_methods.py.

Constructor & Destructor Documentation

__init__()

__init__	(		self,
		*	my_fancy_parameters )

 Just print the passed parameters 

Definition at line 24 of file how_to_use_arbitrary_methods.py.

    def __init__(self, *my_fancy_parameters):
        """ Just print the passed parameters """
        print(my_fancy_parameters)
 

Member Function Documentation

fit()

fit	(		self,
			X,
			y )

 Our method is so good, it doesn't even have to look at the data! 

Definition at line 28 of file how_to_use_arbitrary_methods.py.

    def fit(self, X, y):
        """ Our method is so good, it doesn't even have to look at the data! """
        return self
 

predict()

predict	(		self,
			X )

 Always return 1, this will boost our signal efficiency to the max 

Definition at line 32 of file how_to_use_arbitrary_methods.py.

    def predict(self, X):
        """ Always return 1, this will boost our signal efficiency to the max """
        return np.ones(len(X))
 
 
# These are the hooks you should implement
 
 

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The documentation for this class was generated from the following file:

• mva/examples/python/how_to_use_arbitrary_methods.py