Optimizing Parameters Values of Tree-Based Contrast Subspace Miner using Genetic Algorithm

Abstract

Mining contrast subspace finds contrast subspaces or subspaces where a query object is most similar to a target class but different from other class in a two-class multidimensional data set. Tree-based contrast subspace miner (TB-CSMiner) which employs tree-based likelihood contrast scoring function has been recently introduced to mine contrast subspaces of a query ob-ject by constructing tree from a subspace that is data objects in a subspace space are

Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm

“…TB-CSMiner with optimized parameter values has been proposed which uses genetic algorithm in the optimization process for a particular data set at hand [2]. It generates an initial population of different sets of parameter's values.…”

“…Table 1 tabulates the details of the data sets. Since there is no ground truth contrast subspace provided in the realworld two-class multidimensional numerical data set, the accuracy of the method is assessed based on the classification accuracy on the contrast subspace projected data set as suggested in [1,2].…”

“…In addition to that, it uses the best minimum number of objects MinObjs, small constant values ε, and several number of relevant of features l based on data sets which have been identified in the previous work as shown in Table 3 [2]. However, a smaller number of random subspaces t is used that is 10 to accelerate the mining contrast subspace process.…”

“…Meanwhile, the default parameter setting as suggested in the previous works is used for both tree-based and tree-based with optimized parameter setting [1,2]. Table 4 presents the average percentage of classification accuracy on BCW, PID, Wine, Glass, CMSC, and Wave data sets for classifier J48, NB, SVM, and RF.…”

“…Tree-based contrast subspace mining method has been introduced to identify contrast subspace of query object in two-class multidimensional numerical data set [1,2]. The tree-based contrast subspace method used tree-based likelihood contrast scoring function to estimate the likelihood contrast score of subspaces with respect to a given query object.…”