midterm.py

from sklearn.base import BaseEstimator, ClassifierMixin
class DiscreteNB(BaseEstimator, ClassifierMixin):
    
    def __init__(self):
        self.MLE_array = np.empty()
        BaseEstimator.__init__(self)
        ClassifierMixin.__init__(self)
    
    def get_params(self, deep=True):
        return BaseEstimator.get_params(self, deep=True)
    
    def set_params(self, **params):
        return BaseEstimator.set_params(self, **params)
    
    def score(self, X, y, sample_weight=None):
        #predict
        #get score based on prediction and actual
        #return score
        return ClassifierMixin.score(self, X, y, sample_weight=None)
    
    def fit(self):
        #get MLE from X,y
        #store MLE array
        return
    
    def predict(self):
        #use MLE array and X to return predicted y
        return
    
x_train, y_train
x_test, y_test

dnb = DiscreteNB()

dnb.fit(x_train, y_train)

dnb.score(x_train, y_train)

dnb.score(x_test, y_test)