kNNi
kNNi is a family of extension methods for the k-Nearest Neighbors classifier and regressor designed to operate on evolving data streams or growing datasets. The "i" generally signals incremental, online, or interactive updates that avoid retraining from scratch as new data arrives.
In a typical kNNi setup, the model maintains a dataset of labeled or unlabeled points along with
Applications include real-time classification, regression on streaming data, anomaly detection, and adaptive user modeling. kNNi can
Limitations: like kNN, performance depends on feature scaling and distance metric; high-dimensional data may degrade accuracy;
kNNi is not a single standard algorithm but a category used in literature and software to describe