Machine learning in trading: theory, models, practice and algo-trading - page 2114
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Maxim, how do you set this thing up?
What is id_tl ?
I don't know, I need a link.
Probably the id_tl of the transformed examples simply
Thank you! It all worked out.
I think the right thing - just train convert, because on the test just goes control - so I did, but the result is very strange - the error logloss exceeds 1 on the test sample and grows - how can this be - I'm shocked.
you can try different ways, just to see
here is a good notebook https://www.kaggle.com/rafjaa/resampling-strategies-for-imbalanced-datasets
you can copy and check
I don't know, I need a link.
Probably the idiosyncrasies of the transformed examples just
It's the same article - nothing is clear there.
It's still the same article - nothing is clear there.
it's a copyedit, I gave you a link to the original
You can try different things, just to see
here's a good notebook https://www.kaggle.com/rafjaa/resampling-strategies-for-imbalanced-datasets
you can copy and check.
So this is the original of the article I looked in Russian.
It's a copyedit, I gave you a link to the original.
But what's the point - there is no information anyway - the code was ripped out.
But what's the point - there's still no information - the code is ripped out.
Everything is perfectly written there. I don't have imbalance classes, but I was making them artificially, just to look at
It's all perfectly written there. I don't have imbalance classes, but I was making them artificially, just to look at
It turned out that "Tomek links" method just doesn't equalize the sample - it reduced the number of null lines from 4005 to 3402, that's why I thought it didn't work.
It turned out that "Tomek links" method just doesn't equalize the sample - it reduced the number of null lines from 4005 to 3402, that's why I thought it didn't work.Uh-huh. First you should do oversampling, then tomik
Oversampling does not give us anything yet, but "tomik" has slightly improved the result - it means that there is something in the data, the main thing is to dig properly.
Histogram of models with different quantization settings on the sample.