The process of Ensemble LDA
The Ensemble LDA algorithm is a combination of LDA and CBDBSCAN. Let’s break the process involved down into steps:
- Text preprocessing: Perform any necessary preprocessing steps such as tokenization, stop-word removal, and stemming on the documents.
- LDA training: Build multiple LDA models on the document collection using different random initializations.
- Topic assignment: For each document in the collection, assign a topic distribution based on the trained LDA models. This can be done by calculating the probability of each topic for the document using the LDA models.
- CBDBSCAN: Apply the CBDBSCAN algorithm to cluster the documents based on their assigned topics. CBDBSCAN is an extension of the DBSCAN algorithm that incorporates a checkback step to refine the clustering results. We will learn about DBSCAN and CBDBSCAN in the next section.
- Output: The output of the algorithm is a set of clusters, where each cluster represents a...
