  With the recent rapid progress in the machine-learning (ML), there have
emerged a new approach using the ML methods to the exchange-correlation
functional of density functional theory. In this chapter, we review how the ML
tools are used for this and the performances achieved recently. It is revealed
that the ML, not being opposed to the analytical methods, complements the human
intuition and advance the development toward the first-principles calculation
with desired accuracy.
