KNNmodel.py 文件源码

def train(self, userFeatureTable, ratingsMat):
        userFeatureTable.loc[:, "age"] = userFeatureTable.loc[:, "age"] / 10.
        # ad hoc fix, make sure feature's range is similar
        self.knnModel = NearestNeighbors(n_neighbors=10, algorithm='ball_tree').fit(userFeatureTable)

        # ratingMat is the rating matrix
        self.ratingsMat = ratingsMat
        self.userFeatureTable = userFeatureTable
        self.userIds = self.userFeatureTable.index  # the actual order seen by the knnmodel