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4 questions
0
votes
2
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R - high dimension data using k means clustering [closed]
The dataset is 1000(observations) x 700(variables), After using pca to do dimension reduction, PC150 explained 85% Variance, so I use this (1000 x 150) data to do k means clustering.
This code was ...
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1
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2
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How can I interpret the results of R kmeans function?
I have a large set of data containing the description for 81432 images. These descriptions are generated by an image descriptor which generates a vector (for each image) with 127 positions. So, I have ...
- 333
2
votes
1
answer
668
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Market / Customer Segmentation - Merging two different segmentations
I have a database where each observation is a person. They were questioned on their attitude towards the consumption of X category of product. I have being using K-means to segment this data.
I have ...
- 3,875
3
votes
1
answer
341
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K - means cluster always landing right on top of whole dataset mean
I have a so so sized data set - 30 000 observations. I would like to run K-means on them but to restrict the center(mean) of the data. This is, I would like to push the clusters away from this mean. ...
- 3,875