Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …

Cluster ensembles have been shown to be better than any standard clustering algorithm at
improving accuracy and robustness across different data collections. This meta-learning …

One of the most important tasks in pattern, machine learning, and data mining is
classification problem. Introducing a general classifier is a challenge for pattern recognition …

Membrane proteins perform a variety of functions vital to the survival of organisms, such as
oxidoreductase, transferase or hydrolase. If the type of membrane protein can be detected …

For obtaining the more robust, novel, stable, and consistent clustering result, clustering
ensemble has been emerged. There are two approaches in clustering ensemble …

Abundant data of the patients is recorded within the health care system. During data mining
process, we can achieve useful knowledge and hidden patterns within the data and …

Clustering ensemble, or consensus clustering, has emerged as a powerful tool for improving
both the robustness and the stability of results from individual clustering methods. Weighted …

Clustering as a major task in data mining is responsible for discovering hidden patterns in
unlabeled datasets. Finding the best clustering is also considered as one of the most …

The ensemble clustering tries to aggregate a number of basic clusterings with the aim of
producing a more consistent, robust and well-performing consensus clustering result. The …

Anemia in children is becoming a worldwide problem owing to the unawareness among
people regarding the disease, its causes and preventive measures. This study develops a …