I am currently trying to use discretize to group data into bins.
I would like to group each column of a multi-dimensional data into a bin as if it is one data.
If I use the documentation method as is, the result is
>> a = rand(10):
>> [y, e] = discretize(a,3)
y =
3 1 2 2 2 1 2 3 1 1
3 3 1 1 1 2 1 1 3 1
1 3 3 1 2 2 2 3 2 2
3 2 3 1 2 1 2 1 2 2
2 3 2 1 1 1 3 3 3 3
1 1 2 3 2 2 3 1 1 1
1 2 2 2 2 3 2 1 2 2
2 3 1 1 2 1 1 1 2 2
3 2 2 3 2 2 1 2 1 1
3 3 1 1 2 1 1 2 2 1
e =
0 0.4000 0.8000 1.2000
.
I want to make it look like
y =
3
3
1
1
2
3
2
1
1
1
.
How can I do this?

2 Kommentare

rng default
A = rand(5)
A = 5×5
0.8147 0.0975 0.1576 0.1419 0.6557 0.9058 0.2785 0.9706 0.4218 0.0357 0.1270 0.5469 0.9572 0.9157 0.8491 0.9134 0.9575 0.4854 0.7922 0.9340 0.6324 0.9649 0.8003 0.9595 0.6787
[y, e] = discretize(A, 3)
y = 5×5
3 1 1 1 2 3 1 3 2 1 1 2 3 3 3 3 3 2 2 3 2 3 3 3 2
e = 1×4
0 0.4000 0.8000 1.2000
For this smaller example, what exactly would you want y to look like and how exactly would you compute that exected result? The more specifically you can explain how you would generate your grouping model the easier it will be for us to help you implement it.
dpb
dpb am 30 Mär. 2021
"... as if it is one data"
Maybe the idea is
>> [y,e]=discretize(A(:),3)
y =
3
3
1
3
2
1
1
2
3
3
1
3
3
2
3
1
2
3
2
3
2
1
3
3
2
e =
0 0.4000 0.8000 1.2000
>>
?

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R2019b

Gefragt:

am 30 Mär. 2021

Kommentiert:

dpb
am 30 Mär. 2021

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