Excellent article! Just want to ask how would you usually decide which model to use in this kind of problem? There are too many models to choose from and I always dunno where to start
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Excellent article! Just want to ask how would you usually decide which model to use in this kind of problem? There are too many models to choose from and I always dunno where to start
In this case when I just want to take a look at the hidden structure of data (or fancy name like data mining), unsupervised machine learning should be in place.
If a person is familiar with bitcoin and knows that certain information can help him to make a trading decision, then he should go for supervised machine learning.
Can you explain a little bit about the difference of unsupervised machine language and supervised machine learning? Sorry I am quite new to this haha
In unsupervised machine learning, there is no answer given. Like in my story here, the red dot and blue dot are not given to the machine, the color is assigned after the machine runs its model.
Supervised machine learning means that for every set of data, we assign a 'true answer' to the model. Then the model will try to work out its way to generate some parameters (for example a regression) to predict the next answer by another set of data.
I got it now, very clear explanation, thanks!