  The goal of chemmodlab is to streamline the fitting and assessment pipeline
for many machine learning models in R, making it easy for researchers to
compare the utility of new models. While focused on implementing methods for
model fitting and assessment that have been accepted by experts in the
cheminformatics field, all of the methods in chemmodlab have broad utility for
the machine learning community. chemmodlab contains several assessment
utilities including a plotting function that constructs accumulation curves and
a function that computes many performance measures. The most novel feature of
chemmodlab is the ease with which statistically significant performance
differences for many machine learning models is presented by means of the
multiple comparisons similarity plot. Differences are assessed using repeated
k-fold cross validation where blocking increases precision and multiplicity
adjustments are applied.
