Inferring feature importance with uncertainties in high-dimensional data.
Pål Vegard JohnsenInga StrümkeSigne Riemer-SørensenAndrew Thomas DeWanMette LangaasPublished in: CoRR (2021)
Keyphrases
- high dimensional data
- feature importance
- random forest
- dimensionality reduction
- low dimensional
- nearest neighbor
- high dimensional
- feature selection
- high dimensions
- high dimensionality
- data sets
- similarity search
- relevance feedback
- data analysis
- high dimensional datasets
- dimension reduction
- semi supervised
- manifold learning
- input space
- high dimensional spaces
- data points
- subspace clustering
- nonlinear dimensionality reduction
- lower dimensional
- high dimensional data sets
- knowledge discovery
- linear discriminant analysis
- feature vectors
- computer vision
- real world
- text categorization
- similarity measure
- principal component analysis
- support vector machine
- learning process
- feature space