Machine learning in trading: theory, models, practice and algo-trading - page 3563
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did you even sell the porno car?
You know what I like about you here, I know someone who looks exactly like you, you're a doppelganger.
bought an extremely rare toyota recently))))
So you bought an LC500 after all? ))))) fool.
waaaah, the tax is cosmic.
so you bought an LC500 after all? )))) fool.
No, it's for the masters of life, a personal collection.
I don't know what to do with you here.)
There are normal definitions there too, not a smoker :)
What does that phrase mean, what does it have to do with people harming themselves?
What does that phrase mean, what does it have to do with people harming themselves?
It's a phrase that comes to mind when you have all sorts of interesting thoughts after a binge.
For example, one travelled to Peru, took liana juice and remembered that he was Tutankhamun in his past life.Yandex Alice Answers (Chat GPT)
What is adasyn
ADASYN (Adaptive Synthetic) is a data processing technique that is used to address imbalances in classes when training machine learning models. It works similarly to SMOTE (Synthetic Minority Over-sampling Technique) but takes into account the difficulty of classifying each sample from a minority class. ADASYN generates more synthetic data for samples that are considered more difficult to classify, which helps to improve the quality and accuracy of the model.
How to useADASYNsynthetic data generation
Generating synthetic data using ADASYN involves the following steps:
1. Import the required libraries and data .
2. Define a complexity score function for each sample from the minority class .
3. Create a new array containing the weights for each sample from the minor ity class.
4. Use the complexity score function to calculate the weights .
5. Create new synthetic data using linear interpolation between the selected samples and their randomly selected nearest neighbours from the minority class.
6. Add the synthetic data to the original dataset .
7. Train the machine learning model on the updated dataset .
what is the complexity score function for each minority class sample in adasyn
The difficulty score function for each minority class sample in ADASYN determines how difficult it is to classify. 1
This is usually done by measuring the number of samples from the dominant class in its immediate environment (e.g. among K nearest neighbours). 1
Based on the complexity score, each sample from a minority of classes is assigned a weight that reflects its importance in the process of generating new data. ADASYN generates more synthetic data for those samples considered more difficult to classify. 1
The key idea behind the ADASYN algorithm is to use the density of the distribution as a criterion to automatically decide the required number for each element of a minority subset. This compensates for uneven distribution (unbalanced) of the data.
This is a winged phrase when all sorts of interesting thoughts come into your head after a binge.
For example, one travelled to Peru, took liana juice there and remembered that he was Tutankhamun in his past life.Am I correct, in the aggregate, that this is a hint that my definitions are made/thought of in a state of altered consciousness?
I'd like to understand the joke better.
Yandex Alice Answers (Chat GPT)
What is adasyn
This is certainly interesting, but can you explain the context of what this is getting at?
Did this approach help with your sample where there is a significant class imbalance?