Comparison of mathematical methods of potential modeling
DOI10.1007/S11004-011-9373-2zbMath1247.86011OpenAlexW1964431398MaRDI QIDQ452219
Publication date: 20 September 2012
Published in: Mathematical Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11004-011-9373-2
probabilitylogistic regressionregressionconditional independenceBayes' theoremoddsformula of total probability\(\tau \)-method\(\nu \)-methodartificial neural netsindependence of eventsindependence of random variableslogistic functionlogistic regression with binary (dichotomous) predictor variableslogitsregression with artificial neural netsweights of evidence
Related Items (3)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The nu expression for probabilistic data integration
- The tau model for data redundancy and information combination in earth sciences: theory and application
- Combining knowledge from diverse sources: An alternative to traditional data independence hypotheses
- Numerical methods for generalized least squares problems
- Progress in Geomathematics
- A Multiplicative Formula for Aggregating Probability Assessments
- Evaluating Information Redundancy Through the Tau Model
- Learning representations by back-propagating errors
- Machine Learning for Spatial Environmental Data
- Probability, Frequency and Reasonable Expectation
- The elements of statistical learning. Data mining, inference, and prediction
This page was built for publication: Comparison of mathematical methods of potential modeling