The Maximally Diverse Subset Selection Problem
COMPARATIVE PERFORMANCE OF THREE METAHEURISTIC APPROACHES FOR THE MAXIMALLY DIVERSE GROUPING PROBLEM
... The MDGP is an NP-hard problem and is dif- ficult to solve. The application of exact methods to larger instances of the MDGP is unduly time con- suming. Therefore, heuristic algorithms have been de- veloped for ...
9
Feature subset selection problem on microarray data
... monotonicity assumption. Therefore search of every possible subset is required in order to obtain the optimal feature subset. Since, it is infeasible to do this, clever search algorithms that are based on ...
90
Subset Selection in Regression Analysis
... 4 Subset Selection and Model Building So far we have assumed that the variables that go into the regression equation were chosen in ...actual subset of regressors that should be used in the model ...
92
Subset selection in dimension reduction methods
... long-standing problem in statistics and related areas is how to find a suitable representation of high-dimensional multivariate ...the problem to two or three, at most four, dimensions in order to be able ...
34
Parallel Pareto Optimization for Subset Selection
... Abstract Subset selection that selects a few variables from a large set is a fundamental problem in many ar- ...for Subset Selection (POSS) method is a power- ful approximation solver ...
7
Distributed Column Subset Selection on MapReduce
... the problem of selecting a few data instances that best represent the entire data ...this problem is of a crucial importance in the big data era as it enables data analysts to understand the insights of the ...
10
Gait Feature Subset Selection by Mutual Information
... Feature Subset Selection by Mutual Information Baofeng Guo and ...Feature selection is an important pre-processing step for pattern ...feature selection can help to identify the factors that ...
6
Maximum Volume Subset Selection for Anchored Boxes
... The approach is based on the shifting technique of Hochbaum and Maass [21]. However, there are some non-standard aspects in our application. It is impossible to break the problem into independent subproblems ...
15
Transfer learning through greedy subset selection
... learning problem involving hundreds of ...hypothesis selection and combination, improving the performance on the target ...feature selection and TL algorithms, on the Imagenet, SUN09 and Caltech-256 ...
11
Feature Subset Selection Using a Genetic Algorithm
... feature subset selection problem in automated design of pattern classi ...feature subset selection problem refers the task of identifying and selecting a useful subset of ...
14
Scalable Subset Selection with Filters and Its Applications
... set selection algorithms, namely sequential learning for subset selection (SLSS), that only need to consider a portion of the feature and observation space in a series of small feature ...
155
Diverse near neighbor problem
... latter problem it is known how to construct a small subset of the input point set (a coreset) such that for any set of cluster centers, the costs of clustering the coreset is within a constant factor away ...
7
Evaluation of Feature Subset Selection, Feature Weighting, and Prototype Selection for Biomedical Applications
... 2. Case-Based Classifiers A case-based classifier classifies a sample according to the cases in a case base and selects the most similar case as output of the classifier. A proper similarity measure is necessary to ...
11
Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection
... our subset selection formulation, since the goal in sparse recovery is to recover the true coefficients of the sparse signal, as opposed to our problem of minimizing the prediction error of an ...
34
Feature subset selection and ranking for data dimensionality reduction
... 4 C ONCLUSIONS A new unsupervised learning algorithm has been proposed for feature selection and dimensionality reduction. The main advan- tage of the new algorithm is that the implementation only involves the ...
6
Hypervolume Subset Selection in Two Dimensions: Formulations and Algorithms
... In this article, we propose two different formulations for the two-dimensional case of the HSSP: An integer programming formulation and a k-link shortest path formulation. Both formulations are based on a preprocessing ...
17
Subset Selection from Large Datasets for Kriging Modeling
... this problem, we use two ...the problem, but is unfortunately quite time consuming as we fit a new Kriging model after every added ...uniform subset of n 1 ...above problem really occurs and ...
24
Optimal Features Subset Selection and Classification for Iris Recognition
... promising performance [10]. Support vector classifiers devise a computationally efficient way of learning good separating hyperplane in a high-dimensional feature space. In this work, we apply SVM to classify the iris ...
20
Column Subset Selection, Matrix Factorization, and Eigenvalue Optimization
... • We identify an intriguing connection between Pietsch factorization and the maxcut semi- definite program [GW95]. 1.2. Overview. We focus on the algorithmic version of the Kashin–Tzafriri theorem because it highlights ...
37
Best subset selection via a modern optimization lens
... best subset selection problem of choosing k out of p features in linear regression given n ...best subset solutions for the least ab- solute deviation loss ...
63