Pages that link to "Item:Q5891551"
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The following pages link to Clustering high dimension, low sample size data using the maximal data piling distance (Q5891551):
Displaying 13 items.
- Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data (Q850147) (← links)
- Partition clustering of high dimensional low sample size data based on \(p\)-values (Q961889) (← links)
- Continuum directions for supervised dimension reduction (Q1662921) (← links)
- Subspace rotations for high-dimensional outlier detection (Q2022542) (← links)
- Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settings (Q2048123) (← links)
- Geometric insights into support vector machine behavior using the KKT conditions (Q2074327) (← links)
- Some clustering-based exact distribution-free \(k\)-sample tests applicable to high dimension, low sample size data (Q2140846) (← links)
- Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data (Q3069864) (← links)
- (Q4607908) (← links)
- Mahalanobis distance informed by clustering (Q5006498) (← links)
- Distance-based outlier detection for high dimension, low sample size data (Q5036480) (← links)
- Asymptotic properties of hierarchical clustering in high-dimensional settings (Q6183699) (← links)
- Double data piling: a high-dimensional solution for asymptotically perfect multi-category classification (Q6643296) (← links)
