Algorithm 2:

Estimating the model parameters required to compute ensemble weights using SUEL.CQO

Input:	The assignments ($C_k,k\in \left\{1,\dots ,K\right\}$), sample covariance matrix ($\widehat{R}$), prediction scores $f_i\left(x_t\right),i\in \left\{1,\dots ,M\right\},t\in \left\{1,\dots ,N\right\}$), number of latent groups ($K$)
1.	Formulate the linear system of equations as Equation 5.6.
2.	Solve the constrained quadratic optimization problem in Equation 5.7 to estimate the model parameters ($\widehat{\pi },\widehat{b},\widehat{{\mu }_0}$).
3.	Estimate the accuracy of each prediction score as $w_i=-\frac{b_i{\mu }_k^0}{\pi -(1-\pi )b_i^2{\mu }_k^{0^2}}$.
Output:	Compute the ensemble scores as $g\left(x_t\right)={\sum }_{i=1}^M{w}_i{f}_i\left(x_t\right)$.