Cyclic Repeated Patterns in Sequential Pattern Mining Based on the Fuzzy C-Means Clustering and Association Rule Mining Technique

Abstract

Abstract:The main aim of the proposed method is to remove cyclic repeated patterns in sequential pattern mining. Initially the input dataset is fed to the clustering process, in which fuzzy c means clustering algorithm is used to cluster the available data based on the similar sequential pattern. This approach is able to mine the patterns with the help of association rule mining, here two major tasks are present one is frequent item set generation and rule generation. In frequent item set generation, support and confidence value is evaluated for each pattern. Based on that, the rules are generated in rule generation. After the mining process, the threshold is fixed and based on that repeated cyclic patterns are removed and stored to the database. The performance of the suggested method is evaluated by means of execution time, memory and database difference ratio. The implementation is done with the help of JAVA platform.

Brain Tissue Classification using PCA with Hybrid Clustering Algorithms

“…The simulated 3D MRI brain images [11] are of volume 3mm slice thickness, with 1x1x1 mm 3 as voxel size and voxel resolution of 1mm 3 , images of common size 181 × 217 × 181 voxels are used. MRI brain images are segmented to a number of clusters, the segmentation process of MFCM-ABC is attained by employing the intensity values of the voxel in the cluster as the feature space.…”

“…It's an iterative process and sensitive to noise and other imaging artifacts. The most commonly used method is FCM, which is used for the sequential pattern mining process in data mining and provides the accurate performance when compared to k means clustering method [3].In segmentation of images, clustering is pondered to be image voxel as the data object and in that, each voxel is allocated to a cluster based on their similarity of selected features. The noise interfered is either gaussian or speckle noise and the image capturing equipment itself incorporates salt & pepper noise.…”