discretize.py 文件源码

def fit(self,X,y=None):
        '''
        ?feature_names???????????????
        X: ?????????DataFrame??Series?
        y: ??????Series?
        '''
        if y is None:
            raise Exception('y????')
        dt=sklearn.tree.DecisionTreeClassifier(criterion='entropy',max_depth=self.max_depth,**self.kwds)
        if len(X.shape)==1:
            dt.fit(X.reshape((-1,1)),y)
            cuts=getTreeSplits(dt)
            if cuts is None:
                # ?????????????????????
                cuts=np.array([np.median(X)])
        else:
            cuts=dict()
            if self.feature_names is None:
                try:
                    feature_names=list(X.columns)
                except:
                    feature_names=list(range(X.shape[1]))
            else:
                feature_names=self.feature_names
            for feature in feature_names:
                try:
                    x=X[:,feature]
                except:
                    x=X[feature]
                x=x.reshape((-1,1))
                dt.fit(x,y)
                cut=getTreeSplits(dt)
                if cut is None:
                    cut=np.array([np.median(x)])
                cuts[feature]=cut.copy()
        self.cuts=copy.deepcopy(cuts)
        return self