  The Young's modulus $E$ is the key mechanical property that determines the
resistance of solids to tension/compression. In the present work, the
correlation of the quantity $E$ with such characteristics as the total molar
mass $M$ of alloy components, the number of components $n$ forming an alloy,
the yield stress $\sigma_{y}$ and the glass transition temperature $T_{g}$ has
been studied in detail based on a large set of empirical data for the Young's
modulus of different amorphous metal alloys. It has been established that the
values of the Young's modulus of metal alloys under normal conditions correlate
with such a mechanical characteristic as the yield stress as well as with the
glass transition temperature. As found, the specificity of the ``chemical
formula'' of alloy, which is determined by molar mass $M$ and number of
components $n$, does not affect on elasticity of the material. The machine
learning algorithm identified both the quantities $M$ and $n$ as insignificant
factors in determining $E$. A simple non-linear regression model is obtained
that relates the Young's modulus with $T_{g}$ and $\sigma_{y}$, and this model
correctly reproduces the experimental data for metal alloys of different types.
This obtained regression model generalizes the previously presented empirical
relation $E\simeq49.8\sigma_{y}$ for amorphous metal alloys.
