The composition-based feature vector for each alloy was derived using the CBFV python library. From this library, we have used the Oliynyk elemental descriptor, which consists of 44 elemental properties such as atomic number, atomic weight, period, group, etc. (complete list available in GitHub repository). CBFV featurization scheme uses this Oliynyk descriptor and provides descriptive statistics such as weighted average, range, and variance for alloy compositions. For additional custom featurization, we have incorporated physical metallurgyguided elemental descriptors closely related to yield strength and ultimate tensile strength . These elemental descriptors are atomic radius, Pauling electronegativity, cohesive energy, number of valence electrons, bulk modulus, elastic modulus, shear modulus, rate of change of shear modulus with temperature, melting temperature, maximum solid solubility limit of the elements in niobium, average valence bond strength, bulk electron concentration, lattice constant, Engel's net bonding valence electrons e/a ratio and the mechanical properties test temperature. These elemental descriptor data are collected from the literature and compiled. The feature vector of each alloy was created using a weighted average in the form