Ggthjy

Word or phrase for showing great skill at something without formal training in it

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Knowing when to use pictures over words

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Tikzing a circled star

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Why did the villain in the first Men in Black movie care about Earth's Cockroaches?

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Avoiding morning and evening handshakes

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High pressure canisters of air as gun-less projectiles

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Scikit learn kmeans with custom definition of inertia?

Scikit Learn: KMeans Clustering 3D data over a time period (dimentionality reduction?)How to extract features and classify alert emails coming from monitoring tools into proper category?Kmeans: Between class intertiaScikit-Learn - Learned model description?Categorical data in KmeansUsing GridSearchCV for custom kernel SVM in scikit-learnPassing a custom kernel with more than two arguments into `svm.SVC` in scikit-learnOptimising Kernel parameters using training data in GaussianProcessRegressor of Scikit-learnFind Cluster Diameter and Associated Cluster Points with KMeans Clustering (scikit learn)where does kmeans store its trained model parameters in scikit learn?

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I've coded a small clustering algorithm for time signals using kmeans, which works ok (gives acceptable results).

However, kmeans uses the sum of squared differences. I would like to be able to input instead my own measure of difference, but there doesn't seem to be a way provided by the library to do that.

What would be the easiest way to achieve this? Any other python library which may provide me some way to input instead my own function to define the distance? Or I guess I could instead re-implement the algorithm myself, but I'd rather keep the sci-kit one (since they provide functionalities I want to use such as parallel processing).

scikit-learn clustering k-means

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asked 5 mins ago

Francis VachonFrancis Vachon

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New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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0

$begingroup$

I've coded a small clustering algorithm for time signals using kmeans, which works ok (gives acceptable results).

However, kmeans uses the sum of squared differences. I would like to be able to input instead my own measure of difference, but there doesn't seem to be a way provided by the library to do that.

What would be the easiest way to achieve this? Any other python library which may provide me some way to input instead my own function to define the distance? Or I guess I could instead re-implement the algorithm myself, but I'd rather keep the sci-kit one (since they provide functionalities I want to use such as parallel processing).

scikit-learn clustering k-means

share

asked 5 mins ago

Francis VachonFrancis Vachon

1

New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I've coded a small clustering algorithm for time signals using kmeans, which works ok (gives acceptable results).

However, kmeans uses the sum of squared differences. I would like to be able to input instead my own measure of difference, but there doesn't seem to be a way provided by the library to do that.

What would be the easiest way to achieve this? Any other python library which may provide me some way to input instead my own function to define the distance? Or I guess I could instead re-implement the algorithm myself, but I'd rather keep the sci-kit one (since they provide functionalities I want to use such as parallel processing).

scikit-learn clustering k-means

share

asked 5 mins ago

Francis VachonFrancis Vachon

1

New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share

asked 5 mins ago

Francis VachonFrancis Vachon

1

New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share

asked 5 mins ago

Francis VachonFrancis Vachon

1

New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 5 mins ago

Francis VachonFrancis Vachon

1

New contributor

Francis Vachon is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 5 mins ago

Francis VachonFrancis Vachon

1