ETL processes are responsible for the extraction of data from several sources, their
cleansing, their customization and transformation, and finally, their loading into a data …

Image classification is a well-studied problem where the aim is to categorize given images
into a predefined set of classes. Although there are different approaches for solving the …

Classification is the task of labeling data instances by using a trained system. The data
instances consist of various attributes and in order to train the system, a set of already …

In this study, we propose an ensemble learning architecture called “Cellular Automata
Learning and Prediction”(CALP) model, for classification of handwritten patterns. We further …

Data clustering is a well studied problem, where the aim is to partition a group of data
instances into a number of clusters. Various methods have been proposed for the problem …

In real world there are many examples where synergetic cooperation of multiple entities
performs better than just single one. The same fundamental idea can be found in ensemble …

A cellular automaton (CA) is a discrete computational system which consists of
interconnection of cells that update their state at every time stamp according to some local …

The concern about the software development and maintenance costs increased the interest
in defect predictions. It is possible to create classifiers capable of identifying software …

Data classification is a well studied problem where the aim is to identify the categories in the
data based on a training set. Various machine learning methods have been utilized for the …

Data mining deals with clustering and classifying large amounts of data, in order to discover
new knowledge from the existent data by identifying correlations and relationships between …