منابع مشابه
Margin-Based Feature Selection in Incomplete Data
This study considers the problem of feature selection in in complete data. The intuitive approach is to first impute the missing values, and then apply a standard feature selection method to select relevant features. In this study, we show how to perform feature selection directly, without imputing missing values. We define the objective function of the un certainty margin based feature selecti...
متن کاملMargin-based feature selection for hyperspectral data
A margin based feature selection approach is explored for hyperspectral data. This approach is based on measuring the confidence of a classifier when making predictions on a test data. Greedy feature flip and iterative search algorithms, which attempts to maximise the margin based evaluation functions, were used in the present study. Evaluation functions use linear, zero-one and sigmoid utility...
متن کاملMax-Margin feature selection
Many machine learning applications such as in vision, biology and social networking deal with data in high dimensions. Feature selection is typically employed to select a subset of features which improves generalization accuracy as well as reduces the computational cost of learning the model. One of the criteria used for feature selection is to jointly minimize the redundancy and maximize the r...
متن کاملFeature selection based on loss-margin of nearest neighbor classification
Article history: Received 6 March 2008 Received in revised form 14 August 2008 Accepted 6 October 2008
متن کاملA Novel Feature Selection Algorithm Based on Hypothesis-Margin
Iterative search margin based algorithm(Simba) has been proven effective for feature selection. However, it still has the following disadvantages: (1) the previously proposed model still lacks enough robust to noises; and (2) the given model does not use any global information, in this way some useful discrimination information may be lost and the convergence speed is also influenced in some ca...
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ژورنال
عنوان ژورنال: Journal of Software
سال: 2010
ISSN: 1000-9825
DOI: 10.3724/sp.j.1001.2008.00842