The following pages link to Cluster-based outlier detection (Q2271842):
Displaying 20 items.
- Clustering ellipses for anomaly detection (Q609173) (← links)
- Outlier mining based abnormal machine detection in intelligent maintenance (Q615283) (← links)
- Clustering noise-included data by controlling decision errors (Q744704) (← links)
- Detecting anomaly collections using extreme feature ranks (Q1715864) (← links)
- Initialization of \(K\)-modes clustering using outlier detection techniques (Q1750620) (← links)
- A distributed algorithm for the cluster-based outlier detection using unsupervised extreme learning machines (Q1992535) (← links)
- Methodically unified procedures for a conditional approach to outlier detection, clustering, and classification (Q2127130) (← links)
- A financial fraud detection indicator for investors: an \textit{IDeA} (Q2151647) (← links)
- New node anomaly detection algorithm based on nonnegative matrix factorization for directed citation networks (Q2173140) (← links)
- Banks' business strategies on the edge of distress (Q2241077) (← links)
- Validity indices for clusters of uncertain data objects (Q2241184) (← links)
- Improved approaches for density-based outlier detection in wireless sensor networks (Q2244052) (← links)
- Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection (Q2435711) (← links)
- Quality driven database mining (Q2724142) (← links)
- Two-phase clustering process for outliers detection (Q4795067) (← links)
- Rank-based outlier detection (Q4922649) (← links)
- (Q5875629) (← links)
- Orthogonal nonnegative matrix factorization problems for clustering: a new formulation and a competitive algorithm (Q6601546) (← links)
- Spatial randomness-based anomaly detection approach for monitoring local variations in multimode surface topography (Q6638886) (← links)
- Statistical methods for decision support systems in finance: how Benford's law predicts financial risk (Q6666701) (← links)
