Machine learning in trading: theory, models, practice and algo-trading - page 3442
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What if we remove increments from the sample that do not cover the specified spread.
Or some other filtering methods.
That doesn't make sense to me. I sent you my idea the other day
It's amazing what similar models we were able to train, with very significant randomisation within the algorithm
The kozul just got even more interesting.
It doesn't make sense to me. I sent you my idea the other day
Didn't remember it, I guess.
It is surprising what similar models we were able to train, with very significant randomisation within the algorithm
The kozul just got even more interesting.
It is standard to train on a training sample, tune on a validation sample and test on a test sample of one model.
Do I understand correctly what you are doing in your kozul is :
you train several models on different parts of the test sample and they must all pass the test sample.
Is that all, or are there more details?
The standard is to train on a traine sample, tune on a validation sample , and test on a test sample of one model.
Do I understand correctly what you are doing in your kozul is :
you train several models on different parts of the test sample and they must all pass the test sample.
Is that all, or are there more details?
You CV described it. Only a test sample isn't used for training by definition. It's a test sample 🫥
Oops. I meant Train. I was sleepy.
.
And then I am already trying to separate these classes into trading and non-trading, with low error. And everything is not perfect there yet. The brains are not enough.
I remember we once had a useful argument about HMM and K-means, that they sort of cluster the same or not the same....
do you remember what it was about? To identify market modes.
I remember we once had a useful argument about HMM and K-means, that they sort of cluster the same or not the same.
do you remember what it was about? To identify market modes.
Nowadays it is common to add the word "causal" to everything - and it reads beautifully and with a hint of magic :)
https://github.com/LilJing/causal_hmm?tab=readme-ov-file