Scikit-multiflow

Overview

Implementation

Components

• anomaly_detection: anomaly detection methods.
• data: data stream methods including methods for batch-to-stream conversion and generators.
• drift_detection: methods for concept drift detection.
• evaluation: evaluation methods for stream learning.
• lazy: methods in which generalisation of the training data is delayed until a query is received, i.e., neighbours-based methods such as kNN.
• meta: meta learning methods.
• neural_networks: methods based on neural networks.
• prototype: prototype-based learning methods.
• rules: rule-based learning methods.
• transform: perform data transformations.
• trees: tree-based methods, e.g. Hoeffding Trees which are a type of Decision Tree for data streams.

  History