A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
This paper discusses an extension of PPR to exponential family distributions, called generalized projection pursuit regression (GPPR). ... Projection pursuit regression (PPR) can be used to estimate a smooth function of several variables from noisy and scattered data. ... Several alternative evaluation criteria exist; a general discussion of GCV and related methods applied to nonparametric regression problems can be found in Wahba  and references therein. ...doi:10.1137/s1064827595296574 fatcat:gd7ttnowvzfelkus4gvxorbchm
Acknowledgments This research work of Miroslav Šiman was supported by Project 1M06047 of the Ministry of Education, Youth and Sports of the Czech Republic. ... Projection (Regression) Depth Let us generalize location projection depth, thoroughly investigated in Zuo (2003) , to the points in the general regression setup. ... Besides, the projectional quantile regression of Paindaveine and Šiman (2011a,c) appears very useful for the exact computation of many statistics based on projection pursuit methodology where the same ...doi:10.1080/03610918.2011.560730 fatcat:f6mow5ol5nf35hiiqaziatfpau
Multiple and Generalized Nonparametric Regression
A new method for nonparametric multiple regression is presented. -2-1. ... Although the resulting additive model cannot represent completely general regression surfaces, it is still more general than linear regression in allowing for general smooth functions rather ... Figure la shows Y plotted against X2 (M) PROJECTION PURSUIT REGRESSION* Jerome H. Friedman Stanford Linear Accelerator Center Stanford University Stanford, ...doi:10.4135/9781412985154.n4 fatcat:hjk4gd3l6jbl5oa4gvg2jmaz5i
It combines the projection pursuit classification tree with the projection pursuit regression. ... In this paper, we propose a new tree-structured regression modelthe projection pursuit regression tree.a new tree-structured regression model—the projection pursuit regression tree—is proposed. ... In Section 2, the general tree-based regression methods and the projection pursuit approach are reviewed. The main algorithm of the projection pursuit regression tree is in the Section 3. ...doi:10.3390/app11219885 fatcat:glwntlvmrjg2djgjkirizdfl6q
In this paper, the general form of exploratory projection pursuit is formulated to be an additional constraint for projection pursuit regres- sion. ... , Providence, RI 02912 USA We present a novel classification and regression method that com- bines exploratory projection pursuit (unsupervised training) with pro- jection pursuit regression (supervised ...
Two new algorithms are developed for regression and classification respectively: sparse projection pursuit regression and sparse Jensen-Shannon Boosting. ... The introduced L 1 regularized projection pursuit encourages sparse solutions, thus our new algorithms are robust to overfitting and present better generalization ability especially in settings with many ... Sparse projection pursuit regression Projection pursuit regression (PPR)  extends the basic additive model to allow interactions among the variables by projection pursuit. ...doi:10.1109/cvpr.2008.4587356 dblp:conf/cvpr/ZhangLTS08 fatcat:ysq5jnc3urcf5e2sxy7j43wmsy
Projection pursuit regression follows a similar prescription. ... In Section 7 we relate projection pursuit regression to the projection pursuit technique for cluster analysis presented by Friedman and Tukey (1974) . ...doi:10.1080/01621459.1981.10477729 fatcat:fyr4jvoeq5cezeh7fyyl3lvmve
Meanwhile, the correlation, regression, and mediating effects of different influencing factors were analyzed through a regressive model to quantify the impact of each variable on the unsafe behavior intention ... This is mainly because, in the case of labor buyer's market, the actual salary of workers is not relevant to whether the project is awarded at a low price. ... Pursuit of Pressure from External energy workmates conditions saving TABLE 7 | 7 Regression analysis. ...doi:10.3389/fpsyg.2022.822609 pmid:35465578 pmcid:PMC9024306 fatcat:32rcg6a2zvcqfip5b6pc2hcwxi
We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yield a new family ... Some improved generalization properties are demonstrated on real-world problems. 'Present address: ... In this paper, the general form of exploratory projection pursuit is formulated to be an additional constraint for projection pursuit regression. ...doi:10.1162/neco.19184.108.40.2063 fatcat:4oz4aq5yfnharcozmo6rnzhfsi
In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression (PPR) is one of most applicable methods. ... The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. ... pursuit regression model. ...doi:10.1007/s11589-009-0563-7 fatcat:omadqepyjngxnmegd6b4l5hwey
\Ve present a novel classifica t.ioll and regression met.hod that combines exploratory projection pursuit. ... (unsupervised traiuing) with projection pursuit. regression (supervised t.raining), t.o yield a. nev"' family of cost./complexity penalLy terms . ... In this paper, the general for111 of exploratory projection pursuit is formulated to be an additional constraint for projection pUl'suit regression. ...dblp:conf/nips/Intrator92 fatcat:dhpftxrvvrgx3kdtlo2pnhzbp4
A new method for nonparametric multiple regression is presented. -2-1. ... Although the resulting additive model cannot represent completely general regression surfaces, it is still more general than linear regression in allowing for general smooth functions rather ... Figure la shows Y plotted against X2 (M) PROJECTION PURSUIT REGRESSION* Jerome H. Friedman Stanford Linear Accelerator Center Stanford University Stanford, ...doi:10.2307/2287576 fatcat:3ahsedweirf6thaeze66f2ohh4
model only with projection pursuit regression model. ... This thesis proposes an upper-lower bound interval estimation forecasting method based on projection pursuit regression model. ... Projection pursuit regression Projection Pursuit Regression (PPR)      technology is a new multiple-factor modeling technology that combines Projection Pursuit (PP) and Regression ...doi:10.12783/dtetr/emme2016/9814 fatcat:vk53d7pkv5e6dfglyjfuauqdye
In this work, we consider a projection pursuit model, in which the nonparametric part is driven by an additive Gaussian process regression. ... When M ≥ d, the projection pursuit model is in general non-identifiable; see Figure 3 for an example. ... Projection pursuit Gaussian process regression In this section, we propose a general approach to reconstruct multi-dimensional functions that admits more complicated sparse representations. ...arXiv:2004.00667v2 fatcat:phx47xc35jdedg2yqmf6mm3qp4
The projection pursuit regression algorithm can be considered as a special case of a more general algorithm and placed in the more general setting of a Hilbert space. ... Summary: “Plane-fitting, for example linear regression, principal components or projection pursuit, is treated from a general per- spective. ...
« Previous Showing results 1 — 15 out of 59,192 results