Thanks for the answer!

I still think something is wrong with this correlation checker. I even used this function to randomize the weights a few times, and I got the same correlation error:

def add_random_noise(weights, noise_level=0.01):
    noise = np.random.uniform(-noise_level, noise_level, size=weights.shape)
    return weights + noise

I am pretty sure it's impossible to have 90% correlation in this case.

I am getting the following warning for my strategy:

WARNING! This strategy correlates with other strategies and will be rejected.
Modify the strategy to produce the different output.

I don't understand what I need to do to get the strategy to "produce the different output". I started from the Ridge Classifier strategy, reused most of the function names, but mine is definitely superior since it yields a better Sharpe ratio.

What am I doing wrong?