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sevamoo / SOMPY

A Python Library for Self Organizing Map (SOM)
Apache License 2.0
532 stars 241 forks source link

How can I use this package on google colab? #128

Closed F-Madruga closed 1 year ago

sevamoo commented 3 years ago

I think we need some help to make this library pip installable!

CatChenal commented 3 years ago

There is a solution (tested) without packaging for pip:

!pip install git+https://github.com/sevamoo/SOMPY.git
nanakayhacker commented 1 year ago

Hello Vahid Moosavi,

Thank you for inventing this great sompy package. It was very useful to me. I have been using it for my article publication and it will be referenced duly.

However I have one problem understanding the component planes. My input variables are many, hence deciphering the patterns to associations just from the component planes is very cumbersome. I need help on the sompy command which I can use to get the results from the component planes so I can do statistical inferences on it.

I want to know if there is a way out to get this problem resolved. I will be glad if my requisition is given the due clarification.

Counting on your cooperation. Thank you

Best Regards, John Owusu

nanakayhacker commented 1 year ago

Thank you for this great package. It was very useful to me. However I have one problem understanding the component planes. Please I want to grab the actual data generated for the weights that were used to derive the component planes so I can use them for statistical purposes. I want to get the neural weights used for initialising each input vector. In your use case, the weights were initialised using pca. I want to get those weight vectors for each winning neuron corresponding to their input. In summary I want to get the overall array of values for the component planes

sevamoo commented 1 year ago

Seems there was already a solution suggested here.