Text-Mining

This documentation summarises various text-mining techniques in Python.

Contents:

• 1. Basics in Text-Mining
  • 1.1. Tokenisation
  • 1.2. Vectorization
• 2. Spell Checker
  • 2.1. Jaccard Distance on Trigram
  • 2.2. Jaccard Distance on 4-gram
  • 2.3. Edit Distance
• 3. Text Classificaton
  • 3.1. Add New Features to Vectorizer
  • 3.2. Multi-Nominal Naive Bayes & CountVectorizer
  • 3.3. Multi-Nominal Naive Bayes & TfidfVectorizer
  • 3.4. Support Vector Machine & TfidfVectorizer
  • 3.5. Logistic Regression & TfidfVectorizer
  • 3.6. Logistic Regression & CountVectorizer
• 4. Document Similarity
  • 4.1. Create a Similiarity Function Btw Two Documents
  • 4.2. Assign Scores to New Documents
  • 4.3. Calculate Accuarcy Score
• 5. Topic Modelling
  • 5.1. Latent Dirichlet Allocation
• 6. Resources
• 7. Glossary