Machine learning in trading: theory, models, practice and algo-trading - page 1165
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And the coefficient for shifting the weights? Like, if the most important 1, then their weight is more, or what?
I don't get it. It's an error on the dataset, how much is classified correctly and how much is incorrect.
I don't get it. It is an error on the dataset, how many correctly classified how many incorrectly
That's the point, I need to set a priority, for example, I need to strive for 60% of correct zeros and 30% of correct ones, so I want to understand, what formula can set it and express in one figure.
The thing is, I then need to set a priority, for example, I need to strive for 60% of the correct zeros and 30% of the correct units, that's what I want to understand, what formula can set it and express a single figure.
I don't know, if such a difference it makes sense to have 2 datasets instead of 1
I don't know, if there is such a difference, it probably makes sense to make two datasets instead of one
And what will give two datasets? In addition, I have little observations - in training only about 9 thousand, and will be 4.5, which is very little.
The description of"BalancedAccuracy" says about some coefficients, I can't understand what they are...
Use object/group weights to calculate metrics if the specified value is"true" and set all weights to"1 " regardless of the input data if the specified value is"false". The default value is "true".
"
And what will two datasets do? In addition, I have little observations - in training only about 9 thousand, and will be 4.5, which is very little.
The description of"BalancedAccuracy" says about some coefficients, I can't understand what they are...
Use object/group weights to calculate metrics if the specified value is"true" and set all weights to"1 " regardless of the input data if the specified value is"false". The default value is "true".
"
I have no idea what you do there )))
see formula
TP - true positive, the rest is similar.
Actually, it's just some tool from Yandex you don't want to understand... they're always mimicking Google and xgboost, mediocrity :)
I have no idea what you do there ))))
see formula
TP - true positive, the rest is similar.
What does"use_weights" have to do with it?
What does"use_weights" have to do with it?
I have no idea, it's some kind of crap model, just like Yandex in general
no idea, it's some kind of crap model, just like the whole Yandex
)))
Alas, this is exactly what is needed, but how? The essence is the same - just by sending prices for entry we get one more indicator, which is no better and no worse than the standard indicators
1) You need to create an adaptive indicator adequate to the market...
1" Generate adequate market characteristics
2" to regulate in "on-line" mode indicator parameters according to these characteristics
3" find the best parameters of the indicator on (each bar) according to the current market characteristics (each bar) with the help of technical indicators and OCS testing
This is how I see it
I have no idea, it's some kind of crap model, just like Yandex in general
And in what models can I adjust what I need - the limits of the values of the correct answers?