def first_principal_component(data): guess = [1 for _ in data[0]] # use partial to make the target and grade fncs a variable of w only unscaled_maximizer, _, _ = Ch8.maximize_batch( partial(directional_variance, data), partial(directional_variance_gradient, data), guess,tolerance = 0.00001) return direction(unscaled_maximizer)
def first_principal_component(data): guess = [1 for _ in data[0]] # use partial to make the target and grade fncs a variable of w only unscaled_maximizer, _, _ = Ch8.maximize_batch( partial(directional_variance, data), partial(directional_variance_gradient, data), guess, tolerance=0.00001) return direction(unscaled_maximizer)