Bagging
Natural Language Processing
A simplified text representation that counts word occurrences while ignoring grammar and word order.
Detailed Explanation
The Bag-of-Words Model is a method used in Natural Language Processing to represent text data by counting the frequency of each word within a document, disregarding grammar, syntax, and word order. This approach simplifies text analysis, enabling algorithms to focus on the presence and importance of words for tasks like classification and sentiment analysis.
Use Cases
- •Classifying emails as spam or not based on word frequency patterns.
Related Terms
Other terms in the Natural Language Processing category