Comments (2)
This doesn't sound like a memory error. Though maybe some memory corruption is happening, you could try starting Julia with --check-bounds=yes
to be sure the error does not come from elsewhere.
The relevant code doesn't sound too complex. You could reproduce the problem by calling hclust2
manually (like the function does at the top), and then run the rest of the lines at the REPL. The merge
matrix is probably incorrect in some way, if you can save/post it somewhere it could be helpful for debugging.
from clustering.jl.
Sorry for leaving this issue hanging - I was in a rush and ended up just using Rcall. Alas, I didn't hang on to the underlying data. If this pops up again, will re-open.
from clustering.jl.
Related Issues (20)
- Adjusted Rand Index inconsistency with Python's sklearn implementation HOT 1
- Adjacency-constrained hierarchical clustering? HOT 1
- AssertionError in kmedoids alg HOT 1
- TagBot trigger issue HOT 10
- conflict of "pairwise" in procedure `kmeans.jl` HOT 2
- Get WCSS (Within-Cluster Sum of Square) for optimal number of clusters in kmeans
- -1 silhouette score returned with empty classes HOT 1
- Docs not deployed for tags. HOT 3
- Unexpected behaviour of cutree - bug with :optimallayout? HOT 1
- Providing additional intrinsic evaluation metrices HOT 4
- Common clustering API (i.e., why aren't KShiftsClustering.jl, QuickShiftClustering.jl, QuickShiftClustering.jl SpectralClustering.jl here...?) HOT 7
- Fix warnings for latest Distances.jl HOT 1
- Hclust.order HOT 2
- Link to benchmarks from README?
- WARNING: both StatsBase and Distances export "pairwise!"; uses of it in module Clustering must be qualified HOT 10
- Is this package actively maintained? By who? HOT 2
- Computationally intensive quality measures, :dunn and :sillouette fail on large datasets HOT 1
- quality_index=:davis_bouldin or quality_index=:calinsky_harabasz not supported. HOT 3
- Unnecessary check of dimensions for input?
- AssertionError in K-medoids algorithm
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from clustering.jl.