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Bcubed problem #7

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MinaHeidari opened this issue Apr 27, 2019 · 1 comment
Open

Bcubed problem #7

MinaHeidari opened this issue Apr 27, 2019 · 1 comment

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@MinaHeidari
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With increasing clusters, B-cubed measure accuracy decreases, while the purity measure and rand-index measure increase in the same data, What is the cause? Does B-cubed measure have a decreasing trend with increasing number of clusters?

@Yuri-Nassar
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Yuri-Nassar commented Sep 20, 2020

I was playing with their ground-truth and output example, and I saw that if the output has just one item we got Pr, Re and Fs equal to 1. For example:

#ground-truth data (also called gold-standard data)
ldict = {
"item1": set(["gray", "black"]),
"item2": set(["gray", "black"]),
"item3": set(["gray"]),
"item4": set(["black"]),
"item5": set(["black"]),
"item6": set(["dashed"]),
"item7": set(["dashed"]),
"item8": set(["fk"]),
"item9": set(["dk"]),
"item10": set(["dk"]),
"item11": set(["dk"]),
}

and

cdict = {
"item1": set(["A", "B"]),
# "item2": set(["A", "B"]),
# "item3": set(["A"]),
# "item4": set(["B"]),
# "item5": set(["B"]),
# "item6": set(["C"]),
# "item7": set(["C"]),
}

I read the paper, but I didn't understand the reason for it. So, I expected that it considers the number of items in the ground-truth.

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