Spectroscopic QUasar Extractor and redshift (z) EstimatorSQUEzE I:
  Methodology
  We present SQUEzE, a software package to classify quasar spectra and estimate
their redshifts. SQUEzE is a random forest classifier operating on the
parameters of candidate emission peaks identified in the spectra. We test the
performance of the algorithm using visually inspected data from BOSS as a truth
table. Only 4\% of the sample ($\sim$6,800 quasars and $\sim$11,520
contaminants) is needed for converged training in recommended choices of the
confidence threshold ($0.2<p_{\rm min}<0.7$). For an operational mode which
balances purity and completeness ($p_{\rm min}=0.28$) we recover a purity of
$96.81\pm0.39\%$ ($99.30\pm0.14\%$ for quasars with $z \geq 2.1$) and a
completeness of $96.83\pm0.30\%$ ($98.42\pm0.15\%$ for quasars with $z \geq
2.1$). SQUEzE can be used to obtain a $\approx$100\% pure sample of $z \geq
2.1$. quasars (with $\approx$96\% completeness) by using a confidence threshold
of $p_{\rm min}=0.7$. The estimated redshift error is $1,500{\rm \thinspace
km/s}$ and we recommend that SQUEzE be used in conjunction with an additional
step of redshift tuning to achieve maximum precision. We find that SQUEzE
achieves the necessary performance to replace visual inspection in BOSS-like
spectroscopic surveys of quasars with subsequent publications in this series
exploring expectations for future surveys and alternative methods.
  Keywords: cosmology: observations - quasar: emission lines - quasar:
absorption lines
