Application of the Random Forest Method in Studies of Local Lymph Node Assay Based Skin Sensitization Data
By Shengqiao Li, A. Fedorowicz, Harshinder Singh, S. Soderholm. 2005
65 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computational Theory and Mathematics, Spectroscopy
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Bjoern H Menze
- B. Michael Kelm
- Fred A. Hamprecht
- Peter Bachert
- Wolfgang Petrich
- Uwe Himmelreich
- Ralf Masuch
In Spectroscopy
- Bjoern H Menze
- B. Michael Kelm
- Fred A. Hamprecht
- Peter Bachert
- Wolfgang Petrich
- Uwe Himmelreich
- Ralf Masuch
Citations in the corpus
- A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data (2009, background): “A feature selection based on the random forest classifier [14] has been found to provide multivariate feature importance scores which are relatively cheap to obtain, and which have been successfully applied to high dimensional data, arising from microarrays [15-20], time series [21], even on spectra”