Results 281 to 290 of about 2,020,990 (315)

Review Rating with Joint Classification and Regression Model

2018
Review rating is a sentiment analysis task which aims to predict a recommendation score for a review. Basically, classification and regression models are two major approaches to review rating, and these two approaches have their own characteristics and strength. For instance, the classification model can flexibly utilize distinguished models in machine
Jian Xu, Hao Yin, Lu Zhang, Shoushan Li, Guodong Zhou   +4 more
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Cointegration and forward and spot exchange rate regressions [PDF]

Journal of International Money and Finance, 2000
Abstract We investigate the relationship between cointegration models of the current spot exchange rate, s t , and the current forward rate, f t , and cointegration models of the future spot rate, s t +1 , and f t and the implications of this relationship for tests of the forward rate unbiasedness hypothesis (FRUH).
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Optimal rate of the regularized regression learning algorithm

International Journal of Computer Mathematics, 2011
This paper studies the regularized learning algorithm associated with the least-square loss and reproducing kernel Hilbert space. The target is the error analysis for the regression problem in learning theory. The upper and lower bounds of error are simultaneously estimated, which yield the optimal learning rate. The upper bound depends on the covering
Yongquan Zhang, Feilong Cao, Zongben Xu
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The improved learning rate for regularized regression with RKBSs

International Journal of Machine Learning and Cybernetics, 2016
The investigation on the performance of learning from samples of functions in Banach spaces is a new research field. A key theoretical problem we need to investigate is how the convergence rate is influenced by the geometry property of the Banach spaces.
Huanxiang Liu, Baohuai Sheng, Peixin Ye
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Adaptive rate control using nonlinear regression

IEEE Transactions on Circuits and Systems for Video Technology, 2003
This paper presents a simple, fast, and accurate rate-control algorithm using nonlinear regression that plays a central role in estimation theory. We measure a conditional mean by estimating a joint probability density function (PDF) using Parzen's (1962) window.
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Analysis of fractional turnover rates by exponential regression

Computer Methods and Programs in Biomedicine, 1992
A recent article (Leonhardt et al. Comput. Methods Prog. Biomed. 32 (1990) 345-350) described the analysis of biological turnover data using a model involving an exponential decay from an initial value to a plateau. The authors included a BASIC program for this analysis, claiming that no comparable programs have been published.
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A Comparison of Beta Regression and Copula Regression for Partial Lapse Rate Estimate

In actuarial analysis, it is very useful to analyze the behavior of an interval-bounded random variable, as a percentage, a proportion, or a fraction, conditioned to other explanatory variables. For this kind of variables, considering the presence of bounds, in general in (0,1), the estimate of the conditional mean and/or conditional quantiles is more ...
Baione, Fabio, Biancalana, Davide, Santoro, Andrea   +2 more
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Online Regression with Controlled Label Noise Rate

2017
Many online regression (and adaptive filtering) algorithms are linear, use additive update and designed for the noise-free setting. We consider the practical setting where the algorithm’s feedback is noisy, rather than a clean label. We propose a new family of algorithms which modifies the learning rate based on the noise-variance of the feedback ...
Edward Moroshko, Koby Crammer
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INSTANTANEOUS REGRESSION RATE MEASUREMENTS IN A HYBRID ROCKET

, 2002
RUSSO, ANNAMARIA, CARMICINO C.
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Hazard Rate Regression Using Ordinary Nonparametric Regression Smoothers

Journal of Computational and Graphical Statistics, 1996
Abstract This article proposes a method for nonparametric estimation of hazard rates as a function of time and possibly multiple covariates. The method is based on dividing the time axis into intervals, and calculating number of event and follow-up time contributions from the different intervals.
openaire   +1 more source