All Questions
13 questions
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11
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What are the right metrics to validate the performance of a custom clustering model with three possible outcomes?
I have developed a custom clustering model on top of MiniBatchKmeans, that has three possible outcomes for each data point:
Assign the point to the correct cluster.
Assign the point to the wrong ...
0
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0
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84
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How to save a Higher accurate K-means Model on a unlabelled data based on Any Performance Evaluation Metrics?
I am experimenting on Iris dataset. I am not using the label. I want to save my model based on any Performance Metrics. According to Performance Metrics which model have higher score I am choosing ...
- 51
4
votes
1
answer
900
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How to compare clustering results between "raw" and normalized data
I have a dataset and I would like to apply a clustering algorithm to find some groups. I do not have any label, so it is just wondering if I can find relevant clusters. If it may help, it is ...
- 566
2
votes
1
answer
1k
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Combine two k-means models for better results
I am clustering some pretty fuzzy data with a special k-means like algorithm (a change of algorithm is not an option). Due to random initialization of cluster centers and the fuzziness of the data the ...
- 21
0
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1
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199
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How to evaluate the perforamance of clustering model using python
I have implemented the k means clustering model using python , i would like to know whether my model is perfect or not , so that i want to know which performance metrics is used for clustering model ...
- 23
1
vote
1
answer
62
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What is the technique to measure the performance of the methods clustering?
Given m, p and t non-zero natural numbers:
m is the number of clustering methods,
p is the number of internal measures for cluster validation (i.e halkidi, sd, calinski_harabaz, davies_bouldin...),
t ...
- 333
2
votes
1
answer
233
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Clustering without test set and evaluation
I have to classify some data without any futher prediction (I just need the best clusters on the data).
Do I still have to train-test-split my data or do a kfoldCV?
And how do I evaluate my ...
- 21
2
votes
0
answers
49
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How to compare 2 clustering algorithm? [duplicate]
I have selected 'Nursery' data set from UCI machine learning repository and run 2 different clustering algorithm on, K Means and Hierarchical clustering. How should I compare these to algorithm to see ...
user212984
0
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1
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1k
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Cluster kmeans comparison between two data sets [duplicate]
I have a situation when I try to see if my data set ("sample") is a good representation of a larger data set ("population") that I have. In Stata, I use the cluster ...
- 295
2
votes
2
answers
713
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Mapping k-means cluster centers and origins (measuring k-means accuracy)
Say I generate a dataset $X$: the first $i$ samples follow $x_i\sim N(\mu_1,\Sigma_1^2)$, the next j samples follow $N(\mu_2,\Sigma_2^2)$ and the last $l$ samples from $N(\mu_3,\Sigma_3^2)$. Naturally,...
- 4,027
0
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483
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How to evaluate k-means considering initial conditions when having the ground truth?
I use kernel k-means algorithm with different kernels and want to see which one is the best. The way i do it is to fix the number of $K$ equal to number of classes (ground truth) and check the ...
- 439
1
vote
1
answer
489
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Evaluation of clustering: single cluster solution vs. multiple clusters
There are a few indices out there that help compare competing clustering solutions (e.g., Calinski-Harabasz index and many others).
Is there a popular index/procedure that helps compare a single ...
- 335
2
votes
3
answers
5k
views
Is K-means performance a bottleneck everywhere?
I've read a paper about a sped-up version of k-means:
Ding et al. (2015). Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup.
Now I wonder, is k-means' ...
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