pythonnumpyscikit-learnmulti-dimensional-scaling

sklearn MDS crashes my kernel?

I have a 50,000 x 15 numpy matrix with continuous data. I want to use MDS (Multi-Dimensional Scaling) to scale down to 2 components in order to visualise the data in a 2-D vector space. For some reason, whenever I go to run the MDS on my data, my memory and CPU % increase quite highly and my kernel crashes, telling me I need to restart. Any one run into similar issues or know what may be causing this?

I'm using a MacBook Air, 125GB SSD, 4GB RAM and my development environment is the Spyder IDE.

Thanks

Solution

  • Our current implementation of MDS is based on the smacof method which is too generic. A PCA / SVD might be much faster in many cases. This is planned as a pull request.

    In the mean time you can directly use sklearn.decomposition.RandomizedPCA instead of the MDS class.