Overfitting in K-means2019 Community Moderator ElectionOverfitting in an unsupervised techniqueCan overfitting occur even with validation loss still dropping?Overfitting Naive Bayesinformation leakage when using empirical Bayesian to generate a predictorvalidation/training accuracy and overfittingSignificant overfitting with CVHow to improve loss and avoid overfittingIs my model overfitting when I add new features?Check Overfitting in CNNIs Overfitting always bad?Overfitting - how to detect it and reduce it?
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Overfitting in K-means
2019 Community Moderator ElectionOverfitting in an unsupervised techniqueCan overfitting occur even with validation loss still dropping?Overfitting Naive Bayesinformation leakage when using empirical Bayesian to generate a predictorvalidation/training accuracy and overfittingSignificant overfitting with CVHow to improve loss and avoid overfittingIs my model overfitting when I add new features?Check Overfitting in CNNIs Overfitting always bad?Overfitting - how to detect it and reduce it?
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How do you test your results for overfitting in a k-means run? Some people have said use a training set. I have about 1500 records and about 20 fields.
k-means overfitting
asked Mar 26 at 19:35
guestguest
112
$endgroup$
add a comment |
$begingroup$
How do you test your results for overfitting in a k-means run? Some people have said use a training set. I have about 1500 records and about 20 fields.
k-means overfitting
asked Mar 26 at 19:35
guestguest
112
$endgroup$
1
$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
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– Carl Rynegardh
Mar 26 at 20:03
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@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43
add a comment |
$begingroup$
How do you test your results for overfitting in a k-means run? Some people have said use a training set. I have about 1500 records and about 20 fields.
k-means overfitting
asked Mar 26 at 19:35
guestguest
112
$endgroup$
How do you test your results for overfitting in a k-means run? Some people have said use a training set. I have about 1500 records and about 20 fields.
k-means overfitting
k-means overfitting
asked Mar 26 at 19:35
guestguest
112
asked Mar 26 at 19:35
guestguest
112
asked Mar 26 at 19:35
guestguest
112
asked Mar 26 at 19:35
guestguest
112
asked Mar 26 at 19:35
guestguest
112
112
1
$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
$endgroup$
– Carl Rynegardh
Mar 26 at 20:03
$begingroup$
@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43
add a comment |
1
$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
$endgroup$
– Carl Rynegardh
Mar 26 at 20:03
$begingroup$
@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43
1
1
$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
$endgroup$
– Carl Rynegardh
Mar 26 at 20:03
$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
$endgroup$
– Carl Rynegardh
Mar 26 at 20:03
$begingroup$
@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43
$begingroup$
@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43
add a comment |
0
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$begingroup$
You can't overfit K-Means. It can, however, be non-robust. It's unsupervised learning, not supervised. Keywords for theory: silhouette analysis, elbow method, gap statistics, mutual information
$endgroup$
– Carl Rynegardh
Mar 26 at 20:03
$begingroup$
@CarlRynegardh although this answer shares the same opinion, this answer seems quite reasonable too. We can settle for a subjective overfitting I think!
$endgroup$
– Esmailian
Mar 26 at 20:43