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# derived from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html | |
# explanations are located there : https://www.linkedin.com/pulse/dissociating-training-predicting-latent-dirichlet-lucien-tardres | |
from sklearn.feature_extraction.text import CountVectorizer | |
from sklearn.decomposition import LatentDirichletAllocation | |
import pickle | |
# create a blank model | |
lda = LatentDirichletAllocation() |
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# derived from http://scikit-learn.org/stable/auto_examples/applications/topics_extraction_with_nmf_lda.html | |
# explanations are located there : https://www.linkedin.com/pulse/dissociating-training-predicting-latent-dirichlet-lucien-tardres | |
from sklearn.feature_extraction.text import CountVectorizer | |
from sklearn.decomposition import LatentDirichletAllocation | |
import pickle | |
n_features = 50 | |
n_topics = 2 |
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<!DOCTYPE html> | |
<meta charset="utf-8"> | |
<style type="text/css"> | |
table { | |
font-family: "Helvetica", "Lucida Sans", "Lucida Sans Unicode", "Luxi Sans", Tahoma, sans-serif; | |
box-shadow: 1px 1px 10px rgba(0,0,0,0.5); | |
border-collapse: collapse; | |
border-spacing: 0; | |
} | |
table { |