Machine learning in trading: theory, models, practice and algo-trading - page 3294
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You didn't get the point (it was about kozul), and started pushing FF again. They don't fit in there at all :)
I understand everything. look, I commented on Sanych's post, what exactly caused my desire to write - it's highlighted in bold there.
Matching approximation and optimisation is like Matching an end and a means to an end.
You made a hypothesis. I made my hypothesis.
My hypothesis is that there is a certain threshold after which quantity passes into quality. you have the opposite hypothesis (or I have the opposite hypothesis, if you find the word "opposite" offensive).
In my hypothesis, you have not reached the threshold.
strangely
how can quantity change into quality, they are completely different things? (i.e. bananas turn into grapes, right?).
where on the graph "no one has reached here", that's where almost everyone is partying - i.e. quantity is high, but quality is low.
starting from "no one has reached here" and to the right, the chart can be finished, there will be no growth there, because there is already a quality one and it is at the beginning, i.e. where the red starts to fall. and there are few quality ones, which is true, but it is trueMax has gone completely off the rails, throwing insults left and right again.
strangely
how can quantity change into quality, they are completely different things? (i.e. bananas turn into grapes, right?).
where on the graph "no one has reached here", that's where almost everyone is partying - i.e. quantity is high, but quality is low.
an analogy can be given as an example: if you polish a flat surface of two bars made of different metals, the less roughness, the better the bars slide on each other. if you keep polishing the surfaces, the bars will stick together, molecules will start penetrating each other from the two bars, i.e. there is not a further reduction of friction forces, but on the contrary, a jump-like growth!
1. What does this have to do with optimisation?
2. A counter question 💩 is a neural network an optimiser or an approximator?
1. What does "here" have to do with what?
2. don't you still know that a neural network is an approximator?