Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods
The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- Anomaly detection→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- Classifier chains for multi-label classification→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- kernlab - An S4 Package for Kernel Methods in R→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- Predicting good probabilities with supervised learning→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- On Calibration of Modern Neural Networks→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- GAUSSIAN PROCESSES FOR MACHINE LEARNING→Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likeliho…Legacy edge — source detail unavailable
- On Calibration of Modern Neural Networks→Predicting good probabilities with supervised learningLegacy edge — source detail unavailable
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Anomaly detection | 2009 | 11,511 |
| Classifier chains for multi-label classification | 2011 | 2,307 |
| kernlab - An S4 Package for Kernel Methods in R | 2004 | 1,864 |
| Predicting good probabilities with supervised learning | 2005 | 1,751 |
| On Calibration of Modern Neural Networks | 2017 | 1,741 |
| GAUSSIAN PROCESSES FOR MACHINE LEARNING | 2004 | 1,486 |
Links
Topics
| Gaussian Processes and Bayesian Inference | Computer Science |
| Face and Expression Recognition | Computer Science |
| Neural Networks and Applications | Computer Science |
Is this record sound?
partial
One field of this record is missing or disagrees with another. What is shown below is what the source publishes.
- supports1 author record(s) attached.
- weakensNo references are recorded despite 4,873 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
- neutralThe DOI carries no year to check against.
- supportsA title is present.
Provenance
sha256 648f8491aaceaa34…