Machine learning in trading: theory, models, practice and algo-trading - page 2847
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It's not a histogram, or a histogram in the conventional sense as Pearson invented it.
Would it have made more sense to you if I'd written"bar charts"?
The generally accepted meaning in narrow circles, I should have specified....
Let's get to the heart of the matter :)
Would it make more sense to you if I wrote"bar charts"?
No of course not, because it doesn't look like a bar chart either - the spacing between bars is uneven. If some bars are close together, they usually have a different colour and mean a different value to which the comparison is made.
Commonly accepted meaning in narrow circles, it should have been specified.....
The circle of you alone is wide only from your point of view.
Let's get to the substance of the question :)
The essence of your question so far lies only in its incomprehensible and incorrect formulation.
Of course not, because it doesn't look like a bar chart either - the spacing between bars is uneven. If some bars are close together, they usually have a different colour and mean a different value to which the comparison is made.
Well, what do you propose to call such a graph? Maybe a spectrogram then?
The circle of you alone is wide only from your point of view.
Do you want to make a study on this topic? Open excel and read what a histogram is for a wide range of users.
The essence of your question so far lies only in its incomprehensible and incorrect formulation.
What is not clear - what are predictors or ways of describing graphs?
Well, what do you suggest we call such a graph? How about a spectrogram?
Do you want to do some research on this topic? Open excel and read what a histogram is for the general public.
What is not clear - what are predictors or ways to describe graphs?
At first glance, you have two values displayed that are not particularly related. In such cases, it is common to use a scatter plot.
At first glance, you have two values displayed that are not particularly related. In such cases, a scatter diagram is usually used.
We assume that the value is the same - just look at the red one. Green - the predictor response number is "1" and is always 1 for y.
We consider that the value is the same - just look at the red one. Green - the predictor response number is "1" and is always 1 for y.
Each bar has an X coordinate of base and a Y coordinate of height, so there are two magnitudes. Since they are quite chaotic, you can look at their distribution on a plane - a heat map or something.
Each bar has an X coordinate of base and a Y coordinate of height, so two values. Since they are quite chaotic, you can look at their distribution on a plane - a heat map or something like that.
The x is the ordinal number of the observation, so scattering won't do anything but rotate the graph. What is important here, in my opinion, is the observation in dynamics.
Try to construct a histogram (in the usual conventional sense) for a sample of column heights. You could also try constructing a survival function.
Try to construct a histogram (in the usual conventional sense) for a sample of column heights. You can also try to construct a survival function.
I have built it, and how do you propose to use it?
As for the survival function, I don't understand how to use it.