Clustering for variables with large amount of categories
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I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.
My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.
Please let me know is this method valid.
clustering unsupervised-learning
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$begingroup$
I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.
My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.
Please let me know is this method valid.
clustering unsupervised-learning
New contributor
$endgroup$
add a comment |
$begingroup$
I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.
My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.
Please let me know is this method valid.
clustering unsupervised-learning
New contributor
$endgroup$
I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do not have domain knowledge to group categories that have less than 5% of representation in the dataset.
My idea is that would it be possible to cluster these variables and will it make any sense to do so. For example if there are many variables which have a lot of categories it would be an issue to cluster one variable since as mentioned above the accuracy would be less because of the high number of categories in other variables.
Please let me know is this method valid.
clustering unsupervised-learning
clustering unsupervised-learning
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edited 2 mins ago
Anony-Mousse
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5,155625
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asked 1 hour ago
Michael SchroterMichael Schroter
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