How to find degree of fit in Kmeans++ clustering in python
There are "soft" variants of k-means that allow this.
In particular, fuzzy-c-means (don't ask me why they use c instead of k...)
But beware that the resulting soft assignment is far from a statistical probability. It's just a number that gives some relative weight based on the squared distance, without any strong statistical model.
How to find degree of fit in K-means++ clustering such that it shows how much percentage the inputs are aligned to each clusters. For instance, input A is in cluster 1 for 0.4 and in cluster 2 for 0.6.