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There's some mileage to be got from adapting concepts from graph theory and network analysis to the analysis of simplicial complexes, whether simulated or constructed from data. [This paper](https://w…
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This module should be responsible for generating features top each claim by its graph.
The features can be average centrality - should calculate centrality for each node (author) and save in the cla…
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Okay, I'm just throwing this one out there. But instead of hierarchical clustering, I think it would be cool to think about using a density-based clustering model. I like the idea of using an addition…
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In recent runs against the latest NCBI dataset of Listeria, we've observed large discrepancies between RabbitTClust and NCBI clustering results. Here're a few examples.
1. When distance threshold < …
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Medoid linkage (there are actually multiple with this name, unfortunately) is inspired by the well-known k-meodids clustering concept (Partitioning Around Medoids, PAM), but in a hierarchical way inst…
kno10 updated
6 months ago
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This module should be responsible for generating features for each claim by its graph.
The features can be average centrality - should calculate centrality for each node (author) and save in the clai…
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What metrics might we use to validate clusterings?
Metrics that can be computed from a single cluster fit:
- The within sum of squares to between sum of squares ratio, which measures relative c…
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Feel free to add your papers here.
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Hi Anastasia Reusova,
Recently, I am clustering some ordinary data (data such as '0,1,2,3', the bigger the worse). I tried the cluster method of Kmodes in R and the way you suggested ( cluste…
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To evaluate how well a clustering algorithm produces classifiable features, we need a way to test for statistically significant differences in cluster assignments across classes. Write a t_test functi…