LDA model

Now it's time to build the LDA model. Using the dictionary and corpus, you are ready to discover which topics are present in the Enron emails. With a quick print of words assigned to the topics, you can do a first exploration about whether there are any obvious topics that jump out. Be mindful that the topic model is heavy to calculate so it will take a while to run. Let's give it a try!

This exercise is part of the course

Fraud Detection in Python

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Exercise instructions

Build the LDA model from gensim models, by inserting the corpus and dictionary.
Save the 5 topics by running print topics on the model results, and select the top 5 words.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Define the LDA model
ldamodel = gensim.models.____.____(____, num_topics=5, id2word=____, passes=5)

# Save the topics and top 5 words
topics = ____.____(num_words=____)

# Print the results
for topic in topics:
    print(topic)

Edit and Run Code