Using visual statistical inference to better understand random class separations in high dimension, low sample size data.
Niladri Roy ChowdhuryDianne CookHeike HofmannMahbubul MajumderEun-Kyung LeeAmy L. TothPublished in: Comput. Stat. (2015)
Keyphrases
- statistical inference
- sample size
- data sets
- model selection
- training data
- high dimension
- data points
- small sample
- statistical power
- high dimensional data
- statistical analysis
- data mining techniques
- lower bound
- training examples
- graphical models
- statistical methods
- real valued
- bayesian inference
- least squares
- data analysis
- objective function