  Recently, several deep learning methods are proposed for the gravitational
wave data analysis. One is conditional variational auto encoder (CVAE),
proposed by Gabbard et al. [1]. We study the accuracy of a CVAE in the context
of the estimation of the QNM frequency of the ringdown. We show that the
accuracy of the estimation by the CVAE is better than the matched filtering.
The areas of confidence regions are also compared and it is shown that the CVAE
can return smaller confidence regions. Also, we assess the reliability of the
confidence regions estimated by the CVAE. Our work confirms that the deep
learning method has ability to compete with or overcome the matched filtering.
