Results 1 - 10 of 35,726

An extensive empirical study of feature selection metrics for text classification

by George Forman, Isabelle Guyon, André Elisseeff - J. of Machine Learning Research , 2003
"... Machine learning for text classification is the cornerstone of document categorization, news filtering, document routing, and personalization. In text domains, effective feature selection is essential to make the learning task efficient and more accurate. This paper presents an empirical comparison ..."
Abstract - Cited by 496 (15 self) - Add to MetaCart
in different situations. The results reveal that a new feature selection metric we call ‘Bi-Normal Separation ’ (BNS), outperformed the others by a substantial margin in most situations. This margin widened in tasks with high class skew, which is rampant in text classification problems and is particularly

Understanding and Using Context

by Anind K. Dey - Personal and Ubiquitous Computing , 2001
"... Context is a poorly used source of information in our computing environments. As a result, we have an impoverished understanding of what context is and how it can be used. In this paper, we provide an operational definition of context and discuss the different ways that context can be used by contex ..."
Abstract - Cited by 865 (0 self) - Add to MetaCart
Context is a poorly used source of information in our computing environments. As a result, we have an impoverished understanding of what context is and how it can be used. In this paper, we provide an operational definition of context and discuss the different ways that context can be used

Games with Incomplete Information Played by 'Bayesian' Players, I-III

by John C Harsanyi - MANAGEMENT SCIENCE , 1967
"... The paper develops a new theory for the analysis of games with incomplete information where the players are uncertain about some important parameters of the game situation, such as the payoff functions, the strategies available to various players, the information other players have about the game, e ..."
Abstract - Cited by 787 (2 self) - Add to MetaCart
The paper develops a new theory for the analysis of games with incomplete information where the players are uncertain about some important parameters of the game situation, such as the payoff functions, the strategies available to various players, the information other players have about the game

Self-discrepancy: A theory relating self and affect

by E. Tory Higgins - PSYCHOLOGICAL REVIEW , 1987
"... This article presents a theory of how different types of discrepancies between self-state representations are related to different kinds of emotional vulnerabilities. One domain of the self (actual; ideal; ought) and one standpoint on the self (own; significant other) constitute each type of self-st ..."
Abstract - Cited by 599 (7 self) - Add to MetaCart
-state representation. It is proposed that different types of self-discrepancies represent different types of negative psychological situations that are associated with different kinds of discomfort. Discrepan-cies between the actual/own self-state (i.e., the self-concept) and ideal self-stales (i.e., representations

The illusion of Control

by Ellen J. Langer - Journal of Personality and Social Psychology , 1975
"... A series of studies was conducted to elucidate a phenomenon here referred to as the "illusion of control. " An illusion of control was denned as an ex-pectancy of a personal success probability inappropriately higher than the ob-jective probability would warrant. It was predicted that fact ..."
Abstract - Cited by 607 (1 self) - Add to MetaCart
that factors from skill situa-tions (competition, choice, familiarity, involvement) introduced into chance situations cause individuals to feel inappropriately confident. In Study 1 sub-jects cut cards against either a confident or a nervous competitor; in Study 2 lottery participants were or were not given a

Some informational aspects of visual perception

by Fred Attneave - Psychol. Rev , 1954
"... The ideas of information theory are at present stimulating many different areas of psychological inquiry. In providing techniques for quantifying situations which have hitherto been difficult or impossible to quantify, they suggest new and more precise ways of conceptualizing these situations (see M ..."
Abstract - Cited by 643 (2 self) - Add to MetaCart
The ideas of information theory are at present stimulating many different areas of psychological inquiry. In providing techniques for quantifying situations which have hitherto been difficult or impossible to quantify, they suggest new and more precise ways of conceptualizing these situations (see

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation

by Yee Hwa Yang, Sandrine Dudoit, Percy Luu, Vivian Peng , 2002
"... There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is ..."
Abstract - Cited by 718 (9 self) - Add to MetaCart
There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment

Improving generalization with active learning

by David Cohn, Richard Ladner, Alex Waibel - Machine Learning , 1994
"... Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples ..."
Abstract - Cited by 544 (1 self) - Add to MetaCart
Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples

Valuing American options by simulation: A simple least-squares approach

by Francis A. Longstaff, Eduardo S. Schwartz - Review of Financial Studies , 2001
"... This article presents a simple yet powerful new approach for approximating the value of America11 options by simulation. The kcy to this approach is the use of least squares to estimate the conditional expected payoff to the optionholder from continuation. This makes this approach readily applicable ..."
Abstract - Cited by 517 (9 self) - Add to MetaCart
applicable in path-dependent and multifactor situations where traditional finite difference techniques cannot be used. We illustrate this technique with several realistic exatnples including valuing an option when the underlying asset follows a jump-diffusion process and valuing an America11 swaption in a 20

Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms

by Thomas G. Dietterich , 1998
"... This article reviews five approximate statistical tests for determining whether one learning algorithm outperforms another on a particular learning task. These tests are compared experimentally to determine their probability of incorrectly detecting a difference when no difference exists (type I err ..."
Abstract - Cited by 723 (8 self) - Add to MetaCart
error). Two widely used statistical tests are shown to have high probability of type I error in certain situations and should never be used: a test for the difference of two proportions and a paired-differences t test based on taking several random train-test splits. A third test, a paired-differences
Results 1 - 10 of 35,726