Comments (2)
I'm not sure how sofia-ml implements k-means, but unless they mention otherwise
it's safe to assume that k-means does not use your labels. It is an
unsupervised learning algorithm that just tries to find groups of points close
to each other in the feature space.
Original comment by ida.noeman
on 12 Sep 2013 at 2:49
from sofia-ml.
Correct. Any provided labels are ignored during k-means training.
Original comment by [email protected]
on 27 Dec 2013 at 8:00
- Changed state: Fixed
from sofia-ml.
Related Issues (19)
- simple fix for gcc 4.3 HOT 2
- sf-weight-vector fails unit test HOT 1
- problems building sofia-ml HOT 1
- malloc error with --hash_mask_bits HOT 1
- Multi-Label Passive-Aggressive
- Training Data Format and Class Label for kmeans HOT 1
- sf-sparse-vector.cc bug, in Init function HOT 1
- Assertion failure in sf-kmeans-methods_test
- Does sofia-ml support other values for features than "1"? HOT 1
- Issues with dimensionality off-by-one HOT 1
- The ids in cluster output are formatted scientific notation rather than ints
- lambda parameter not passed into SvmObjective correctly
- sofia doesnt work on sparse dataset containing lines in which all features are 0
- Various errors in source code
- Assertion '!cluster_centers_empty()' fails and crashes program HOT 1
- Multi-label classification
- sofia-kmeans diverging with increasing number of iterations?
- make all_test : Assertion `x1.GetGroupId() == "2"' failed
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