def maximizeStochastic_list(targetFn, gradientFn, x, y, theta0, alpha0=0.01): # Only change from above, uses minimizeStochastic_list instead of minimizeStochastic return minimizeStochastic_list(negate(targetFn), negateAll(gradientFn), x, y, theta0, alpha0)
def maximizeStochastic(targetFn, gradientFn, x, y, theta0, alpha0=0.01): return minimizeStochastic(negate(targetFn), negateAll(gradientFn), x, y, theta0, alpha0)