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140,934
Feature selection: Evaluation, application, and small sample performance
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... Abstract—A large number of algorithms have been proposed for feature subset selection. Our experimental results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. We study the problem of choosing an optimal feature s ..."
Abstract
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Cited by 474 (13 self)
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feature selection in small sample size situations. Index Terms—Feature selection, curse of dimensionality, genetic algorithm, node pruning, texture models, SAR image classification. 1
1 Self-controlled case series analyses: small sample performance
"... We derive second-order expressions for the asymptotic bias and variance of the log relative incidence estimator for the self-controlled case series method in a simplified scenario, and study in qualitative terms how bias and variance depend on factors such as the relative incidence and ratio of risk ..."
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of risk to observation period. Small-sample performance of the estimator in realistic scenarios is investigated using simulations. We find that in scenarios likely to arise in practice, asymptotic methods are valid for numbers of cases in excess of 20 – 50 depending on the ratio of the risk period
SMOTE: Synthetic Minority Over-sampling Technique
- Journal of Artificial Intelligence Research
, 2002
"... An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentag ..."
Abstract
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Cited by 634 (27 self)
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good means of increasing the sensitivity of a classifier to the minority class. This paper shows that a combination of our method of over-sampling the minority (abnormal) class and under-sampling the majority (normal) class can achieve better classifier performance (in ROC space) than only under-sampling
Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, With an Application to the PPP Hypothesis; New Results. Working paper
, 1997
"... We examine properties of residual-based tests for the null of no cointegration for dynamic panels in which both the short-run dynamics and the long-run slope coefficients are permitted to be heterogeneous across individual members of the panel+ The tests also allow for individual heterogeneous fixed ..."
Abstract
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Cited by 529 (13 self)
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fixed effects and trend terms, and we consider both pooled within dimension tests and group mean between dimension tests+ We derive limiting distributions for these and show that they are normal and free of nuisance parameters+ We also provide Monte Carlo evidence to demonstrate their small sample size
Improving Direct-Mapped Cache Performance by the Addition of a Small Fully-Associative Cache and Prefetch Buffers
, 1990
"... ..."
Empirical exchange rate models of the Seventies: do they fit out of sample?
- JOURNAL OF INTERNATIONAL ECONOMICS
, 1983
"... This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar exch ..."
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Cited by 854 (12 self)
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This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar
The Cache Performance and Optimizations of Blocked Algorithms
- In Proceedings of the Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
, 1991
"... Blocking is a well-known optimization technique for improving the effectiveness of memory hierarchies. Instead of operating on entire rows or columns of an array, blocked algorithms operate on submatrices or blocks, so that data loaded into the faster levels of the memory hierarchy are reused. This ..."
Abstract
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Cited by 574 (5 self)
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given cache size, the block size that minimizes the expected number of cache misses is very small. Tailoring the block size according to the matrix size and cache parameters can improve the average performance and reduce the variance in performance for different matrix sizes. Finally, whenever possible
Incorporating non-local information into information extraction systems by Gibbs sampling
- IN ACL
, 2005
"... Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling, ..."
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Cited by 730 (25 self)
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Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling
Tobins Q, corporate diversification and firm performance
, 1993
"... In this paper, we show that Tobin's q and firm diversification are negatively related. This negative relation holds for different diversification measures and when we control for other known determinants of q. We show further that diversified firms have lower q's than equivalent portfolios ..."
Abstract
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Cited by 499 (26 self)
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portfolios of specialized firms. This negativerelation holds throughout the 1980s in our sample. Finally, it holds for firms that have kept their number of segments constant over a number of years as well as for firms that have not. In our sample, firms that increase their number of segments have lower q
Support Vector Machine Classification and Validation of Cancer Tissue Samples Using Microarray Expression Data
, 2000
"... Motivation: DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data ..."
Abstract
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Cited by 569 (1 self)
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Motivation: DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data
Results 1 - 10
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140,934
