High dimensional feature selection under interactive models

... popularity of high dimensional feature selection High dimensional feature selection aims at selecting relevant features from the suspected high dimensional feature space by removing redundant features ... feasible feature selection procedures under the high dimensional feature space by considering both the main effect features and the interactive effect featu...

Ngày tải lên: 10/09/2015, 09:08

... important to mention that, in feature selection under the small-n-largep situation in high- dimensional studies, an assumption associated with feature selection in high- dimensional studies is “sparsity” ... Part I includes Chapters 2, 3, 4, In Chapter 2, we introduce EBIC in detail In Chapter 3, we examine the selection consistency of the EBIC in feature s...

Ngày tải lên: 09/09/2015, 10:19

... therein In this thesis, we are particularly interested in the highdimensional correlation matrix estimation problem with missing observations in factor models As a tool for dimensionality reduction, ... correction procedure to deal with the correlation matrix estimation problem with missing observations in strict factor models where the sparse component tur...

Ngày tải lên: 09/09/2015, 11:08

... Joint Feature Selection in Distributed Stochastic Learning The following discussion of learning methods is based on pairwise ranking in a Stochastic Gradient Descent (SGD) framework The resulting ... from scaling discriminative training for SMT to large training sets We deploy generic features for SCFG-based SMT that can efficiently be read off from rules at runtime...

Ngày tải lên: 19/02/2014, 19:20

... ingredients: feature selection and order identification Feature selection was formalized as a constrained optimization problem, the output of which was a set of important features to determine word senses ... counting second order co-occurrence was 50 words 3.2 Evaluation method for feature selection For evaluation of feature selection, we used mutual information bet...

Ngày tải lên: 20/02/2014, 16:20

... need the bits to code the index of the feature (i.e., which feature from amongst the total m candidate features) and the bits to code the coefficient of this feature The total cost can be represented ... feature selection algorithm, we code lf by using log(m) bits (where m is the total number of candidate features), which is equivalent to the standard RIC (or the Bonferroni penalty...

Ngày tải lên: 17/03/2014, 02:20

... presents our progressive feature selection algorithm that greatly extends the feature space for conditional maximum entropy modeling The new algorithm is able to select features from feature space ... the SGC algorithm, we propose a progressive feature selection algorithm that selects features in multiple rounds The main idea of the PFS algorithm is to split the fe...

Ngày tải lên: 17/03/2014, 04:20

... select features, is quite natural We note, however, that kernels are calculated using the DP algorithm Therefore, it is not clear how to calculate kernels efficiently with a statistical feature selection ... 2003 Word-Sequence Kernels Journal of Machine Learning Research, 3:1059–1082 M Collins and N Duffy 2001 Convolution Kernels for Natural Language In Proc of Neural Inf...

Ngày tải lên: 23/03/2014, 19:20

... vary between and 1, and the corrected Rand index (Hubert and Arabie, 1985; Denœud and Gu´ noche, 2006): e RC = r − Exp(r) Max(r) − Exp(r) 0.03 0.01 Corrected Rand Index 0.04 0.05 The clustering ... i and POS- tag n-gram k, ni• = k nik and n•k = i nik ) are transformed in this manner: eik √ (1) yik = √ − ρk fi ρk where eik = nik /n are the relative counts, fi = ei• = ni• /n (r...

Ngày tải lên: 24/03/2014, 03:20

... decrease the feature numbers without losing classification accuracies (see G Forman 2003 An extensive empirical study of feature selection metrics for text classification The Journal of Machine ... numbers of features are to be selected, different combinations of the two measurements are required to provide the best performance Although a great number of FS methods is av...

Ngày tải lên: 30/03/2014, 23:20

... create a model as the predictor Combining SVMs with Various Feature Selection Strategies 3 Feature Selection Strategies In this Section, we discuss feature selection strategies tried during the competition ... of features Combining SVMs with Various Feature Selection Strategies b) Use RF as a predictor and conduct 5-fold CV on the working set c) Update...

Ngày tải lên: 24/04/2014, 13:03

... discard the least informative features based on the amount of information that each feature carries regarding the output classes presence of feature i and a value of "0 " indicated its absence in ... of data collected over an interval containing the movement onset (measured as the finger switch activation) if no artifact was detected in that particular interva...

Ngày tải lên: 19/06/2014, 10:20

... September in all the nurseries and trial sites in three years (2006-2008) Ongoing informal training also continues in all of the participating nurseries especially since staff and technicians are gaining ... to undertake the study tour in 2007 Prof Choob, Prof Bunvong and Prof Monton of Kasetsart University, who are helping to arrange a tour of Macadamia plan...

Ngày tải lên: 21/06/2014, 04:20

... 1 Institute Information Project Name Establish nurseries and training to effectively propagate high quality trees and trial plantation models of Macadamia in provinces of North Vietnam Vietnamese ... frames In addition, again the work of FSI as well as that of other Macadamia initiatives, including that of WASI and Thiabinh Foods, are be...

Ngày tải lên: 21/06/2014, 06:20