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where does kmeans store its trained model parameters in scikit learn?


Scikit Learn: KMeans Clustering 3D data over a time period (dimentionality reduction?)Finding parameters with extreme values (classification with scikit-learn)Does scikit-learn use regularization by default?How to get the inertia at the begining when using sklearn.cluster.KMeans and MiniBatchKMeansHow does scikit-learn decision function method work?Binomial model in scikit-learnHow to set parameters to search in scikit-learn GridSearchCVFind Cluster Diameter and Associated Cluster Points with KMeans Clustering (scikit learn)Confused about how to graph my high dimensional dataset with KmeansHow to force weights to add to $1$ in Linear regression













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Like in linear regression, there is model.intercept_ and model.coef_ but in kmeans i found kmeans.inertia_ , I dont know what is that.










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    $begingroup$


    Like in linear regression, there is model.intercept_ and model.coef_ but in kmeans i found kmeans.inertia_ , I dont know what is that.










    share|improve this question







    New contributor




    Akhilesh is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      Like in linear regression, there is model.intercept_ and model.coef_ but in kmeans i found kmeans.inertia_ , I dont know what is that.










      share|improve this question







      New contributor




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







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      Like in linear regression, there is model.intercept_ and model.coef_ but in kmeans i found kmeans.inertia_ , I dont know what is that.







      python scikit-learn k-means machine-learning-model






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      asked 16 hours ago









      AkhileshAkhilesh

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          K-means stores 4 model parameters namely cluster_centers_, labels_, inertia_, n_iter_. For details on what they store you can look at the official documentation. Also, Inertia, or the within-cluster sum of squares criterion, can be recognized as a measure of how internally coherent clusters are. You can see a full description here under the section: 2.3.2. K-means.






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            $begingroup$

            K-means stores 4 model parameters namely cluster_centers_, labels_, inertia_, n_iter_. For details on what they store you can look at the official documentation. Also, Inertia, or the within-cluster sum of squares criterion, can be recognized as a measure of how internally coherent clusters are. You can see a full description here under the section: 2.3.2. K-means.






            share|improve this answer









            $endgroup$


















              1












              $begingroup$

              K-means stores 4 model parameters namely cluster_centers_, labels_, inertia_, n_iter_. For details on what they store you can look at the official documentation. Also, Inertia, or the within-cluster sum of squares criterion, can be recognized as a measure of how internally coherent clusters are. You can see a full description here under the section: 2.3.2. K-means.






              share|improve this answer









              $endgroup$
















                1












                1








                1





                $begingroup$

                K-means stores 4 model parameters namely cluster_centers_, labels_, inertia_, n_iter_. For details on what they store you can look at the official documentation. Also, Inertia, or the within-cluster sum of squares criterion, can be recognized as a measure of how internally coherent clusters are. You can see a full description here under the section: 2.3.2. K-means.






                share|improve this answer









                $endgroup$



                K-means stores 4 model parameters namely cluster_centers_, labels_, inertia_, n_iter_. For details on what they store you can look at the official documentation. Also, Inertia, or the within-cluster sum of squares criterion, can be recognized as a measure of how internally coherent clusters are. You can see a full description here under the section: 2.3.2. K-means.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered 15 hours ago









                bkshibkshi

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