Mathematical methods in artificial intelligence
Mathematical methods in artificial intelligence
Statistical Models in S
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
PCA and SVD with nonnegative loadings
Pattern Recognition
Two-parameter ridge regression and its convergence to the eventual pairwise model
Mathematical and Computer Modelling: An International Journal
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Effects of attribute reducing on real-estate valuation
MMES'10 Proceedings of the 2010 international conference on Mathematical models for engineering science
Mathematical and Computer Modelling: An International Journal
| Hi-index | 0.98 |
Multiple linear regression with special properties of its coefficients parameterized by exponent, logit, and multinomial functions is considered. To obtain always positive coefficients the exponential parameterization is applied. To get coefficients in an assigned range, the logistic parameterization is used. Such coefficients permit us to evaluate the impact of individual predictors in the model. The coefficients obtained by the multinomial-logit parameterization equal the shares of the predictors, which is useful for interpretation of their influence. The considered regression models are constructed by nonlinear optimization techniques, have stable solutions and good quality of fit, have simple structure of the linear aggregates, demonstrate high predictive ability, and suggest a convenient way to identify the main predictors.