We analyze an extremely deep 450-$mu$m image ($1sigma=0.56$,mJy,beam$^{-1}$) of a $simeq 300$,arcmin$^{2}$ area in the CANDELS/COSMOS field as part of the SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). We select a robust (signal-to-noise ratio $geqslant 4$) and flux-limited ($geqslant 4$,mJy) sample of 164 sub-millimeter galaxies (SMGs) at 450-$mu$m that have $K$-band counterparts in the COSMOS2015 catalog identified from radio or mid-infrared imaging. Utilizing this SMG sample and the 4705 $K$-band-selected non-SMGs that reside within the noise level $leqslant 1$,mJy,beam$^{-1}$ region of the 450-$mu$m image as a training set, we develop a machine-learning classifier using $K$-band magnitude and color-color pairs based on the thirteen-band photometry available in this field. We apply the trained machine-learning classifier to the wider COSMOS field (1.6,deg$^{2}$) using the same COSMOS2015 catalog and identify a sample of 6182 450-$mu$m SMG candidates with similar colors. The number density, radio and/or mid-infrared detection rates, redshift and stellar mass distributions, and the stacked 450-$mu$m fluxes of these SMG candidates, from the S2COSMOS observations of the wide field, agree with the measurements made in the much smaller CANDELS field, supporting the effectiveness of the classifier. Using this 450-$mu$m SMG candidate sample, we measure the two-point autocorrelation functions from $z=3$ down to $z=0.5$. We find that the 450-$mu$m SMG candidates reside in halos with masses of $simeq (2.0pm0.5) times10^{13},h^{-1},rm M_{odot}$ across this redshift range. We do not find evidence of downsizing that has been suggested by other recent observational studies.
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