Metadata-Version: 2.1
Name: ktLDA
Version: 0.0.6
Summary: An implementation of latent Dirichlet allocation
Home-page: https://github.com/cPolaris/ktLDA
Author: Kehan (kehanLyu) & Tiangang (cPolaris)
Author-email: 
License: UNKNOWN
Description: # ktLDA
        
        This is an implementation of Latent Dirichlet Allocation for pedagogical purposes.
        
        ### Dependencies
        
        - numpy
        - tqdm
        
        ### Examples
        
        ```python
        from ktlda import KtLDA
        import pickle
        
        with open('ourdata-cleaned.pickle', 'rb') as f:
            comp, rec = pickle.load(f)
        X = comp + rec
        Y = [0] * len(comp) + [1] * len(rec)
        
        lda = KtLDA(n_components=2, alpha=0.5, beta=0.5, iterations=10, max_vocab=5000, random_state=663)
        lda.fit(X)
        print(lda.doc_topic_dist)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
