Machine Learning Models

Machine Learning Models for PII Detection

1. Supervised Learning:
   • Training Data: Models are trained on labeled datasets that include examples of PII such as names, email addresses, phone numbers, and more.
   • Algorithms: Common ML algorithms like Random Forest, Gradient Boosting Machines, or Support Vector Machines (SVMs) are applied to classify text and identify PII.

2. Unsupervised Learning:
   • Clustering: Tools like k-means or hierarchical clustering group sensitive data patterns without pre-labeled datasets.
   • Anomaly Detection: Identifies unusual patterns in datasets that might indicate the presence of PII.

3. Feature Engineering:
   • Developing specific features such as regular expressions, word embeddings, or token patterns to enhance the detection of PII.