R: how to visualize categorical data?

What out-of-core dimension reduction algorithms, available in python, should I use to help visualize big data?

  • My Challenge: to process Cluster Million of documents in unsupervised algorithm. And visualize them . Entering each cluster , I want to Visualize Centroids and documents.     My Weapons: scikit-learn , and d3 for HTML5 visualization, and I use HashingVectorizer + Minibatch Kmeans to solve memory problem for clustering, as explained here http://scikit-learn.org/dev/auto_examples/applications/plot_out_of_core_classification.html. RandomizedPCA is senseless to run on Chunked data.      Is there any out-of-core Dimension Reduction Algorithm in python that can be applied on scipy sparse matrices ?. I am looking for a Python based solution - so not interested in incorporating external data structures, such as Hadoop.

  • Answer:

    Would any (not "out of core" implemented) techniques help? (I'm interested in it myself)

Dan Ofer at Quora Visit the source

Was this solution helpful to you?

Just Added Q & A:

Find solution

For every problem there is a solution! Proved by Solucija.

  • Got an issue and looking for advice?

  • Ask Solucija to search every corner of the Web for help.

  • Get workable solutions and helpful tips in a moment.

Just ask Solucija about an issue you face and immediately get a list of ready solutions, answers and tips from other Internet users. We always provide the most suitable and complete answer to your question at the top, along with a few good alternatives below.