聚类与降维
61 种方法属于此方法族。
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主动学习关联规则Active learning association rules combines the iterative query-and-label loop of active learning with association rule mining, allowing a human expert to guide the discovery proces主动学习自编码器异常检测Active Learning Autoencoder Anomaly Detection combines an autoencoder's unsupervised reconstruction-error scoring with an active learning query loop. The model flags high-error ins主动学习孤立森林Active Learning Isolation Forest combines the unsupervised anomaly-scoring power of Isolation Forest with an iterative query strategy that asks a human expert to label the most inf亲和传播聚类Affinity propagation, introduced by Brendan Frey and Delbert Dueck in 2007, is a clustering algorithm that identifies representative 'exemplars' among the data by exchanging messagApriori算法The Apriori algorithm, introduced by Agrawal and Srikant in 1994, is the foundational method for discovering frequent itemsets and association rules in transactional databases. It 关联规则挖掘（Apriori）Association Rule Mining is an unsupervised data-mining technique that discovers co-occurrence patterns among items in transactional datasets. Formally introduced by Agrawal, Imieli
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全部方法 61
主动学习关联规则主动学习自编码器异常检测主动学习孤立森林亲和传播聚类Apriori算法关联规则挖掘（Apriori）关联规则自动编码器异常检测BIRCHDBSCANECLAT 频繁项集挖掘集成先验算法 (Ensemble Apriori Algorithm)集成关联规则集成自编码器异常检测Ensemble HDBSCAN集成孤立森林集成K均值模糊 C均值聚类 (FCM)高斯混合模型HDBSCAN层次聚类孤立森林 (Isolation Forest)K-means聚类K-Means聚类核主成分分析局部异常因子 (LOF)局部线性嵌入 (LLE)均值漂移单类支持向量机在线关联规则在线自编码器异常检测在线 DBSCAN在线HDBSCAN在线孤立森林 (Online Isolation Forest)在线K均值聚类 (Online K-means)OPTICS主成分分析主成分回归 (PCR)随机投影正则化高斯混合模型正则化 K-均值聚类鲁棒自编码器异常检测Robust HDBSCAN鲁棒隔离森林鲁棒k均值自组织映射 (Kohonen 映射)自监督自编码器异常检测自监督 DBSCAN自监督高斯混合模型自监督隔离森林自监督 K-均值半监督Apriori算法半监督关联规则半监督自编码器异常检测半监督DBSCAN半监督 HDBSCAN半监督隔离森林半监督K-均值谱聚类t-SNEUMAP