Data vs Centroid Agreement in skfuzzy C-Mean
data.shape
#(6741, 6)
centroid.shape
#(10, 6)
cntr, u, u0, d, jm, p, fpc = fuzz.cluster.cmeans(data.T, 10, 2, `error=0.00005, maxiter=100,init = centroid)`
Error:
shapes (10,6) and (6741,6) not aligned: 6 (dim 1) != 6741 (dim 0)
If I transpose centroid
operands could not be broadcast together with shapes (6,10) (10,10)
(6,10)
No. of data points = 6741. Features = 6. Classes = 10
So centroid should be (10,6) dimensions right? Why is it expecting 6741?
python-3.x scikit-learn
asked Nov 12 at 10:07
Martan
203
add a comment |
data.shape
#(6741, 6)
centroid.shape
#(10, 6)
cntr, u, u0, d, jm, p, fpc = fuzz.cluster.cmeans(data.T, 10, 2, `error=0.00005, maxiter=100,init = centroid)`
Error:
shapes (10,6) and (6741,6) not aligned: 6 (dim 1) != 6741 (dim 0)
If I transpose centroid
operands could not be broadcast together with shapes (6,10) (10,10)
(6,10)
No. of data points = 6741. Features = 6. Classes = 10
So centroid should be (10,6) dimensions right? Why is it expecting 6741?
python-3.x scikit-learn
asked Nov 12 at 10:07
Martan
203
In the desription it is saidinit : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.
– hellpanderr
Nov 12 at 10:46
u0is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects
– hellpanderr
Nov 12 at 10:49
add a comment |
data.shape
#(6741, 6)
centroid.shape
#(10, 6)
cntr, u, u0, d, jm, p, fpc = fuzz.cluster.cmeans(data.T, 10, 2, `error=0.00005, maxiter=100,init = centroid)`
Error:
shapes (10,6) and (6741,6) not aligned: 6 (dim 1) != 6741 (dim 0)
If I transpose centroid
operands could not be broadcast together with shapes (6,10) (10,10)
(6,10)
No. of data points = 6741. Features = 6. Classes = 10
So centroid should be (10,6) dimensions right? Why is it expecting 6741?
python-3.x scikit-learn
asked Nov 12 at 10:07
Martan
203
data.shape
#(6741, 6)
centroid.shape
#(10, 6)
cntr, u, u0, d, jm, p, fpc = fuzz.cluster.cmeans(data.T, 10, 2, `error=0.00005, maxiter=100,init = centroid)`
Error:
shapes (10,6) and (6741,6) not aligned: 6 (dim 1) != 6741 (dim 0)
If I transpose centroid
operands could not be broadcast together with shapes (6,10) (10,10)
(6,10)
No. of data points = 6741. Features = 6. Classes = 10
So centroid should be (10,6) dimensions right? Why is it expecting 6741?
python-3.x scikit-learn
python-3.x scikit-learn
asked Nov 12 at 10:07
Martan
203
asked Nov 12 at 10:07
Martan
203
asked Nov 12 at 10:07
Martan
203
asked Nov 12 at 10:07
Martan
203
asked Nov 12 at 10:07
Martan
203
203
In the desription it is saidinit : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.
– hellpanderr
Nov 12 at 10:46
u0is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects
– hellpanderr
Nov 12 at 10:49
add a comment |
In the desription it is saidinit : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.
– hellpanderr
Nov 12 at 10:46
u0is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects
– hellpanderr
Nov 12 at 10:49
In the desription it is said
init : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.– hellpanderr
Nov 12 at 10:46
In the desription it is said
init : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.– hellpanderr
Nov 12 at 10:46
u0 is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects– hellpanderr
Nov 12 at 10:49
u0 is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects– hellpanderr
Nov 12 at 10:49
add a comment |
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In the desription it is said
init : 2d array, size (S, N); N is the number of data sets; S is the number of features within each sample vector.– hellpanderr
Nov 12 at 10:46
u0is the centroid matrix, you can run cmeans on your data without initialization and inspect it to understand the format algorithm expects– hellpanderr
Nov 12 at 10:49