Pages that link to "Item:Q2254437"
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The following pages link to Sparse partial least squares classification for high dimensional data (Q2254437):
Displaying 23 items.
- Partial least squares with a regularized weight (Q283784) (← links)
- On partial least squares dimension reduction for microarray-based classification: a simulation study (Q956938) (← links)
- PLS and dimension reduction for classification (Q964596) (← links)
- An asymmetric classifier based on partial least squares (Q991957) (← links)
- Kernel logistic PLS: a tool for supervised nonlinear dimensionality reduction and binary classifi\-cation (Q1020063) (← links)
- Generalized orthogonal components regression for high dimensional generalized linear models (Q1663286) (← links)
- High-dimensional clustering via random projections (Q2129311) (← links)
- Variable selection of spectroscopic data through monitoring both location and dispersion of PLS loading weights (Q2132036) (← links)
- How can we identify the sparsity structure pattern of high-dimensional data: an elementary statistical analysis to interpretable machine learning (Q2170515) (← links)
- Envelope-based sparse partial least squares (Q2176612) (← links)
- Penalized partial least square applied to structured data (Q2189327) (← links)
- Partial least squares classification for high dimensional data using the PCOUT algorithm (Q2255855) (← links)
- PLS for Big Data: a unified parallel algorithm for regularised group PLS (Q2323935) (← links)
- A sparse PLS for variable selection when integrating omics data (Q2864004) (← links)
- (Q3096110) (← links)
- Classification of sparse high-dimensional vectors (Q3559954) (← links)
- Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection (Q4632618) (← links)
- Correlated Component Regression: Re-thinking Regression in the Presence of Near Collinearity (Q4973039) (← links)
- A Review of Envelope Models (Q6064133) (← links)
- Nonparametric classification of high dimensional observations (Q6201367) (← links)
- A Bayesian framework for pathway-guided identification of cancer subgroups by integrating multiple types of genomic data (Q6560524) (← links)
- Equality tests of covariance matrices under a low-dimensional factor structure (Q6667486) (← links)
- High-dimensional sparse classification using exponential weighting with empirical hinge loss (Q6668598) (← links)
