Algorithm 1 ADASYN

Input:  Imbalanced training data $\left(x_i,y_i\right)$ Output:  Synthetic data in minority class $\left(u_i\right)$ 1:$S=\left(A_{maj}-A_{min}\right)·v$ 2:${\rho }_i={\gamma }_i/K$ 3:$\overline{{\rho }_i}={\rho }_i/\sum {\gamma }_i$ 4:$g_i=\beta ·\overline{{\rho }_i}$ 5:for$i<g_i$do 6:    $x_{zi}=randomlySelect\left(x_i\right)$ 7:    $u_i=x_i+rand\left(0,1\right)·\left(x_{zi}-x_i\right)$ 8:end for 9:return$u_i$