Module advanced 

Cutting-edge clustering algorithms including quantum-inspired methods and advanced online learning.

This module provides state-of-the-art clustering algorithms that push the boundaries of traditional clustering methods. It includes quantum-inspired algorithms that leverage quantum computing principles and advanced online learning variants with concept drift detection.

Features

• Quantum K-means: Uses quantum superposition principles for potentially better optimization
• Adaptive Online Clustering: Automatically adapts to changing data distributions
• Concept Drift Detection: Detects and adapts to changes in streaming data
• Dynamic Cluster Management: Creates, merges, and removes clusters automatically
• Quantum Annealing: Simulated quantum annealing for global optimization Cutting-edge clustering algorithms including quantum-inspired methods and advanced online learning

This module provides implementations of state-of-the-art clustering algorithms that push the boundaries of traditional clustering methods. It includes quantum-inspired algorithms that leverage quantum computing principles, advanced online learning variants, reinforcement learning approaches, transfer learning methods, and deep clustering techniques.

Examples

Quantum-Inspired Clustering

use scirs2_cluster::advanced::quantum::{quantum_kmeans, QuantumConfig};
use scirs2_core::ndarray::Array2;

let data = Array2::from_shape_vec((10, 2), (0..20).map(|x| x as f64).collect()).unwrap();
let config = QuantumConfig::default();
let (centroids, labels) = quantum_kmeans(data.view(), 3, Some(config)).unwrap();

Adaptive Online Clustering

use scirs2_cluster::advanced::online::{adaptive_online_clustering, AdaptiveOnlineConfig};
use scirs2_core::ndarray::Array2;

let data = Array2::from_shape_vec((20, 3), (0..60).map(|x| x as f64).collect()).unwrap();
let config = AdaptiveOnlineConfig::default();
let (centers, labels) = adaptive_online_clustering(data.view(), Some(config)).unwrap();

Re-exports

pub use online::adaptive_online_clustering;

pub use online::AdaptiveOnlineClustering;

pub use online::AdaptiveOnlineConfig;

pub use quantum::quantum_kmeans;

pub use quantum::QuantumConfig;

pub use quantum::QuantumKMeans;

pub use quantum::QuantumState;

pub use deep::*;

pub use quantum_algorithms::*;

pub use reinforcement::*;

pub use transfer::*;

Modules

deep

Deep clustering algorithms

online

Adaptive online clustering with concept drift detection

quantum

Quantum-inspired clustering algorithms

quantum_algorithms

Quantum algorithm implementations for clustering

reinforcement

Reinforcement learning-based clustering algorithms

transfer

Transfer learning clustering algorithms

Functions

default_adaptive_online_config

Convenience function to create a default adaptive online configuration

default_quantum_config

Convenience function to create a default quantum configuration

quick_online_clustering

Convenience function for quick online clustering with default parameters

quick_quantum_clustering

Convenience function for quick quantum clustering with default parameters