Linked Questions
12 questions linked to/from Chosing optimal k and optimal distance-metric for k-means
57
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11
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How to decide on the correct number of clusters?
We find the cluster centers and assign points to k different cluster bins in k-means clustering which is a very well known algorithm and is found almost in every machine learning package on the net. ...
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87
votes
6
answers
147k
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Why does k-means clustering algorithm use only Euclidean distance metric?
Is there a specific purpose in terms of efficiency or functionality why the k-means algorithm does not use for example cosine (dis)similarity as a distance metric, but can only use the Euclidean norm? ...
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25
votes
8
answers
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Perform K-means (or its close kin) clustering with only a distance matrix, not points-by-features data
I want to perform K-means clustering on objects I have, but the objects aren't described as points in space, i.e. by objects x features dataset. However, I am able ...
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19
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4
answers
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k-means implementation with custom distance matrix in input
Can anyone point me out a k-means implementation (it would be better if in matlab) that can take the distance matrix in input?
The standard matlab implementation needs the observation matrix in input ...
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17
votes
3
answers
31k
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Choosing optimal K for KNN
I performed a 5-fold CV to select the optimal K for KNN. And it seems like the bigger K gets, the smaller the error...
Sorry I didn't have a legend, but the different colors represent different ...
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11
votes
1
answer
17k
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Elbow criteria to determine number of cluster
It is mentioned here that one of the methods to determine the optimal number of clusters in a data-set is the "elbow method". Here the percentage of variance is calculated as the ratio of the between-...
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20
votes
1
answer
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How to define number of clusters in K-means clustering?
Is there any way to determine the optimal cluster number or should I just try different values and check the error rates to decide on the best value?
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9
votes
3
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Using k-means with other metrics
So I realize this has been asked before: e.g. What are the use cases related to cluster analysis of different distance metrics? but I've found the answers somewhat contradictory to what is suggested ...
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2
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2
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5k
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How to determine optimal number of clusters?
For a multilabel dataset, i would like to find the number of clusters involved in it. The below example gives more details about the problem:
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- 4,097
0
votes
2
answers
1k
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Distance function for categories in K-means
How to define a distance function when euclidean distance doesn't apply? For instance, say I have some data involves nationality. I'll probably assign a number to each nation, but for nations that ...
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-1
votes
1
answer
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Determining number of clusters K-means [duplicate]
I would like to automatically determine the number of clusters for K-means. I have read that elbow method could be used for that.
The thing that confuses me is - I have to rerun algorithm while ...
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1
vote
1
answer
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How To Determine Number Of Clusters In T-SNE And Best Clustering Algorithm?
I used TSNE method to cluster my DataSet.
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