Results 221 to 230 of about 2,868,550 (249)
Some of the next articles are maybe not open access.
Annals of Operations Research, 1995
We take a regression-based approach to the problem of induction, which is the problem of inferring general rules from specific instances. Whereas traditional regression analysis fits a numerical formula to data, we fit a logical formula to boolean data. We can, for instance, construct an expert system for fitting rules to an expert's observed behavior.
Boros, E., Hammer, P. L., Hooker, J. N.
openaire +2 more sources
We take a regression-based approach to the problem of induction, which is the problem of inferring general rules from specific instances. Whereas traditional regression analysis fits a numerical formula to data, we fit a logical formula to boolean data. We can, for instance, construct an expert system for fitting rules to an expert's observed behavior.
Boros, E., Hammer, P. L., Hooker, J. N.
openaire +2 more sources
2004
The main problem with localized discriminant techniques is the curse of dimensionality, which seems to restrict their use to the case of few variables. This restriction does not hold if localization is combined with a reduction of dimension. In particular it is shown that localization yields powerful classifiers even in higher dimensions if ...
Tutz, Gerhard, Binder, Harald
openaire +2 more sources
The main problem with localized discriminant techniques is the curse of dimensionality, which seems to restrict their use to the case of few variables. This restriction does not hold if localization is combined with a reduction of dimension. In particular it is shown that localization yields powerful classifiers even in higher dimensions if ...
Tutz, Gerhard, Binder, Harald
openaire +2 more sources
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1998
AbstractA new approach in nonparametric regression is to use the signs of the residuals ri = yi ‐ θ (xi) in the regression modell yi = θ (xi) + ϵi instead of the residuals itself. It turns out, that with a suitable definition of complexity of the noise ϵi we are able to determine the minimum number of local extrema and turning points for the regression
openaire +2 more sources
AbstractA new approach in nonparametric regression is to use the signs of the residuals ri = yi ‐ θ (xi) in the regression modell yi = θ (xi) + ϵi instead of the residuals itself. It turns out, that with a suitable definition of complexity of the noise ϵi we are able to determine the minimum number of local extrema and turning points for the regression
openaire +2 more sources
Biostatistics, 2023
SummaryAssessing how brain functional connectivity networks vary across individuals promises to uncover important scientific questions such as patterns of healthy brain aging through the lifespan or dysconnectivity associated with disease. In this article we introduce a general regression framework, Connectivity Regression (ConnReg), for regressing ...
Neel Desai +3 more
openaire +2 more sources
SummaryAssessing how brain functional connectivity networks vary across individuals promises to uncover important scientific questions such as patterns of healthy brain aging through the lifespan or dysconnectivity associated with disease. In this article we introduce a general regression framework, Connectivity Regression (ConnReg), for regressing ...
Neel Desai +3 more
openaire +2 more sources
Multiple Regression—Regression Diagnostics
2004In Chapter 9 we show how to set up and produce an initial analysis of a regression model with several predictors. In the present chapter we discuss ways to investigate whether the model assumptions are met and, when the assumptions are not met, ways to revise the model to better conform with the assumptions. We also examine ways to assess the effect on
Richard M. Heiberger, Burt Holland
openaire +1 more source
Journal of Biopharmaceutical Statistics, 2005
Adjustment for prognostic covariates is recommended in clinical trials because relative to a t-test, it improves precision and adjusts for treatment imbalances caused by an "unlucky" randomization. But, inclusion of too many covariates can be counterproductive.
Michael A, Proschan +2 more
openaire +2 more sources
Adjustment for prognostic covariates is recommended in clinical trials because relative to a t-test, it improves precision and adjusts for treatment imbalances caused by an "unlucky" randomization. But, inclusion of too many covariates can be counterproductive.
Michael A, Proschan +2 more
openaire +2 more sources
Regression und Anti-Regression
Zeitschrift für psychoanalytische Theorie und Praxis, 2007The authors describe an anti-regressive function of the ego, which in everyday life maintains a mature functional level and in psychoanalytic works takes the form of resistance. The authors stress the necessity of creating a climate during analysis that permits a controlled relaxation of the anti-regressive function.
J. Sandler, A. Sandler
openaire +1 more source
Regression and unbiased regression
Trabajos de Estadistica Y de Investigacion Operativa, 1978A method of evaluation of the efficiency of a regression function is given. Unbiased regression is defined. In annex, a method of computation of mean values is given, which is very useful in many cases.
openaire +1 more source