klotz: clustering* + k-means* + nlp* + python*

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  1. tokenizing and stemming each synopsis transforming the corpus into vector space using tf-idf calculating cosine distance between each document as a measure of similarity clustering the documents using the k-means algorithm using multidimensional scaling to reduce dimensionality within the corpus plotting the clustering output using matplotlib and mpld3 conducting a hierarchical clustering on the corpus using Ward clustering plotting a Ward dendrogram topic modeling using Latent Dirichlet Allocation (LDA)

    2018-08-16 Tags: , , , , , , , by klotz

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