MyFancyClassifier Class Reference

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

def __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()

def 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()

def 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