Machine learning in trading: theory, models, practice and algo-trading - page 3434
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h ttps:// www.ixbt.com/news/2024/03/14/ipad-4-cerebras-wse-3.html
it's nice to see the progress of microelectronics.
my speciality ;)
I share the results, so tree [3,3,3,3] - each level in the leaf is clustered into 3 clusters, total 3 levels, in the end 27 final leaves.
We apply the result on 3 samples - test and exam did not participate in the tree construction.
The graph below shows the shift of target "1" in per cent relative to the average value of target "1" in its sample - for each leaf of the tree.
What is pleasing is the stability of the offset, i.e. where there was more than 0 or 1 on the train, it often remains on the other samples.
However, if we take examples in the train sample with an offset of more than 5%, we get only about 20% of examples from the whole sample, which is not enough.
some fashion for clustering is going on....
I created an algorithm for automatic identification of trades based on clustering )
works...
Would you say no?
I share the results, so tree [3,3,3,3] - each level in the leaf is clustered into 3 clusters, for a total of 3 levels, resulting in 27 final leaves.
We apply the result on 3 samples - test and exam did not participate in tree construction.
The graph below shows the shift of target "1" in per cent relative to the average value of target "1" in its sample - for each leaf of the tree.
What is pleasing is the stability of the offset, i.e. where there was more than 0 or 1 on the train, it often remains the same on the other samples.
However, if we take examples in the train sample with an offset of more than 5%, we get only about 20% of examples from the whole sample, which is not enough.
What if we divide it into 27 clusters without trees? Will the result change?
there's this clustering thing going on...
I created an algorithm for automatic identification of pro-trades based on clustering )
works...
would you say no?
It looks very interesting. Any details?
And if we divide it into 27 clusters without trees? Will the result change?
Good question. I think the result will change in numerical terms, but qualitatively the trend will remain the same, i.e. the stability features.
Now I'm going to count 27 clusters at once, at the same time I'll check my algorithm for adequacy of performance with such a truncated tree in essence
When I thought of making a tree, the idea was that clusters should be evenly distributed in the process of building a tree over a multidimensional space, rather than it would happen randomly.
And this is how the leaves of the 3-3-3-3 tree look like, below are separate graphs for each sample - in the order of train, test, exam
Well, we can see that the probability shift in the leaves is already larger, but instability is also beginning to appear. The percentage of examples in positive leaves of the tree (clusters) decreased in the subsequent samples, which once again confirms the uniqueness of combinations characteristic of a certain section of the trade. I note that the sample is complex - only 10% of units (positive target units).