Results 311 to 320 of about 10,283,828 (367)
Some of the next articles are maybe not open access.
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
Regressing and Regressed Melanoma
2004Malignant melanoma frequently undergoes regression (10–35% of cases), and on occasion, this can be extensive. Regressed areas can vary from foci only a few rete ridges in breadth to being subtotal or even complete. Only about 40 cases of completely regressed primary melanoma are on record, but this is doubtless a huge underestimation.
Guido Massi, Philip E. LeBoit
openaire +1 more source
On regressing regression coefficients
Journal of Statistical Planning and Inference, 1982This paper considers a regression model in which coefficients obtained from a previous regression are themselves the object of analysis. It is shown that the parameters of interest can be obtained in two ways: pooling across observations and subsamples, or a two-stage process of first estimating the coefficients within each subsample, and then using ...
openaire +2 more sources
2007
The Medical Subject Headings (MeSH) thesaurus used by the National Library of Medicine defines logistic regression models as "statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable ...
Todd G, Nick, Kathleen M, Campbell
openaire +2 more sources
The Medical Subject Headings (MeSH) thesaurus used by the National Library of Medicine defines logistic regression models as "statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable ...
Todd G, Nick, Kathleen M, Campbell
openaire +2 more sources
Linear Regression and Logistic Regression
2023Supervised learning is a machine learning task of mapping the input to the output on the basis of labeled input-output example pairs. Supervised learning may be of two types: classification and regression. In this chapter, we will discuss linear regression in one variable, linear regression in multiple variables, gradient descent, and polynomial ...
Deepti Chopra, Roopal Khurana
openaire +1 more source
The Ocular Surface, 2009
©2009 Ethis Communications, Inc. The Ocular Surface ISSN: 1542-0124. Novack GD, Crockett RS. Regression to the mean. 2009;7(3):163-165. W e are frequently involved in evaluating studies of new ophthalmology agents. The efficacy of some treatments can be measured in mm Hg with a tonometer or by letters on an eye chart.
Gary D, Novack, R Stephens, Crockett
openaire +2 more sources
©2009 Ethis Communications, Inc. The Ocular Surface ISSN: 1542-0124. Novack GD, Crockett RS. Regression to the mean. 2009;7(3):163-165. W e are frequently involved in evaluating studies of new ophthalmology agents. The efficacy of some treatments can be measured in mm Hg with a tonometer or by letters on an eye chart.
Gary D, Novack, R Stephens, Crockett
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
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
Theory of Probability & Its Applications, 1964
A study is made of certain properties of an approximation to the regression line on the basis of sampling data when the sample size increases unboundedly.
openaire +3 more sources
A study is made of certain properties of an approximation to the regression line on the basis of sampling data when the sample size increases unboundedly.
openaire +3 more sources
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