Pages that link to "Item:Q1175399"

The following pages link to Multivariate adaptive regression splines (Q1175399):

Displaying 50 items.

• Using boosting to prune double-bagging ensembles (Q961263) (← links)
• Boosting nonlinear additive autoregressive time series (Q961660) (← links)
• Generalized profiling estimation for global and adaptive penalized spline smoothing (Q961675) (← links)
• Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography (Q961895) (← links)
• Penalized spline estimation for functional coefficient regression models (Q962336) (← links)
• A new nonlinear classifier with a penalized signed fuzzy measure using effective genetic algorithm (Q962684) (← links)
• MARS: selecting basis functions and knots with an empirical Bayes method (Q964645) (← links)
• A metric multidimensional scaling-based nonlinear manifold learning approach for unsupervised data reduction (Q966949) (← links)
• Simultaneous confidence band and hypothesis test in generalised varying-coefficient models (Q972894) (← links)
• Least angle and \(\ell _{1}\) penalized regression: a review (Q975564) (← links)
• A new approach to linear regression with multivariate splines (Q976235) (← links)
• Parametric and nonparametric empirical regression models: case study of copper bromide laser generation (Q980642) (← links)
• Some comments on a bridge between nonlinear dynamicists and statisticians (Q994957) (← links)
• Nonparametric estimation when data on derivatives are available (Q997381) (← links)
• A mixture of experts model for rank data with applications in election studies (Q999671) (← links)
• Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms (Q1006921) (← links)
• Theoretical framework for local PLS1 regression, and application to a rainfall data set (Q1010485) (← links)
• Choice of B-splines with free parameters in the flexible discriminant analysis context (Q1010528) (← links)
• Efficient estimation of adaptive varying-coefficient partially linear regression model (Q1012226) (← links)
• A method for improving the accuracy of data mining classification algorithms (Q1017461) (← links)
• Spatial interpolation of high-frequency monitoring data (Q1018619) (← links)
• On multi-view learning with additive models (Q1018621) (← links)
• Parsimonious additive models (Q1019916) (← links)
• Knot selection by boosting techniques (Q1020124) (← links)
• Secure computation with horizontally partitioned data using adaptive regression splines (Q1020679) (← links)
• SCAD-penalized regression in high-dimensional partially linear models (Q1020975) (← links)
• Varying-coefficient single-index model (Q1023472) (← links)
• Semi-parametric nonlinear regression and transformation using functional networks (Q1023546) (← links)
• Tree-structured smooth transition regression models (Q1023576) (← links)
• Stepwise feature selection using generalized logistic loss (Q1023708) (← links)
• A flexible approach to Bayesian multiple curve fitting (Q1023881) (← links)
• Increasing the usefulness of additive spline models by knot removal (Q1023906) (← links)
• Gaussian processes and limiting linear models (Q1023934) (← links)
• A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory (Q1033416) (← links)
• Stochastic design optimization: application to reacting flows (Q1033536) (← links)
• Coupled aerostructural design optimization using the Kriging model and integrated multiobjective optimization algorithm (Q1035939) (← links)
• On multicollinearity and concurvity in some nonlinear multivariate models (Q1039952) (← links)
• Genetic learning of fuzzy rules based on low quality data (Q1040932) (← links)
• Adaptive hinging hyperplanes and its applications in dynamic system identification (Q1049096) (← links)
• Robustness of reweighted least squares kernel based regression (Q1049548) (← links)
• The analysis of survey data (Q1130018) (← links)
• A Thurstonian pairwise choice model with univariate and multivariate spline transformations (Q1261625) (← links)
• Application of orthogonal arrays and MARS to inventory forecasting stochastic dynamic programs. (Q1285809) (← links)
• Practical selection of neighbourhoods for local regression in the bivariate case (Q1315201) (← links)
• Cointegration tests on MARS (Q1318307) (← links)
• A theory for memory-based learning (Q1342731) (← links)
• Neural networks and logistic regression: Part I (Q1351182) (← links)
• Bivariate B-splines for tensor logspline density estimation (Q1351843) (← links)
• Locally adaptive regression splines (Q1355186) (← links)
• \(M\)-type regression splines involving time series (Q1360970) (← links)