Recent advances in technology has led to huge growth in generating high dimensional data sets by capturing millions of facts in various fields, time phases, localities and brands. Microarray data contains gene expression from thousands of genes (features) from only tens of hundreds of samples. The rich source of information generated from microarray experiments often consist of incomplete and/o...

The paper presents model based on fuzzy methods for churn prediction in retail banking. The study was done on the real, anonymised data of 5000 clients of a retail bank. Real data are great strength of the study, as a lot of studies often use old, irrelevant or artificial data. Canonical discriminant analysis was applied to reveal variables that provide maximal separation between clusters of ch...

The size of web has increased exponentially over the past few years with thousands of documents related to a subject available to the user. With this much amount of information available, it is not possible to take the full advantage of the World Wide Web without having a proper framework to search through the available data. This requisite organization can be done in many ways. In this paper w...

In this paper, we apply K-means and Fuzzy C-Means, two widely used clustering algorithms, to cluster a lymph node tissue section which had been diagnosed with metastatic infiltration (cancer spread from its original location). Each cluster algorithm is run 10 times as different initialisation states may lead to different clustering results. We compare the performance of the two algorithms by su...

1106 | P a g e Abstract--Image processing plays an important role in medical field because of its capability. Particularly, image segmentation offer several guides in medical field for analyzing the captured image. Usually, the medical images are captured via different medical image acquisition techniques. The captured image may be affected by noise because of some faults in the capturing devis...

Spectroscopy or hyperspectral imaging consists in the acquisition, analysis, and extraction of the spectral information measured on a specific region or object using an airborne or satellite device. Hyperspectral imaging has become an active field of research recently. One way of analysing such data is through clustering. However, due to the high dimensionality of the data and the small distanc...

In this paper, a new Hopfield-model net called Compensated Fuzzy Hopfield Neural Network (CFHNN) is proposed for vector quantization in image compression. In CFHNN, the compensated fuzzy c-means algorithm, modified from penalized fuzzy cmeans, is embedded into Hopfield neural network so that the parallel implementation for codebook design is feasible. The vector quantization can be cast as an o...

Image segmentation and classification are two important steps in multicolor fluorescence in-situ hybridization (MFISH) images analysis. In this paper we first developed an improved adaptive fuzzy c-means (IAFCM) algorithm for the segmentation of the DAPI channel of M-FISH images to extract interested regions for the following classification task. Then we employed a sparse representation-based c...

Traditionally, supervised machine learning methods are the first choice for tasks involving classification of data. This study provides a non-conventional hybrid alternative technique (pEAC) that blends the Possibilistic Fuzzy CMeans (PFCM) as base cluster generating algorithm into the ‘standard’ Evidence Accumulation Clustering (EAC) clustering method. The PFCM coalesces the separate propertie...

† Department of Electronics & Communication Engineering, S.R.K. Institute of Technology, Vijayawada, India †† Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Hyderabad, India ††† Department of Electronics & Communication Engineering, Amrita Sai institute of Science & Technology, Paritala, India. Summary This paper presents an algorithm for the e...