Abstract: The information age needs to master the technique of data mining, the data were analyzed. The classification and prediction through data mining can grasp the basic trend of the development ...

In traditional fault diagnosis methods in power systems, it is difficult to accurately classify and predict the types of faults. With the emergence of big data technology, the fault classification and ...

Keywords: tunnel boring machine, rock mass classification, operational data mining, Gaussian mixture model, K-nearest neighbor. Citation: Sun M, Chen S, He H, Wang W, Song K and Lin X (2024) ...

interpret the contribution of data warehousing and data mining to the decision-support level of organizations. evaluate different models used for OLAP and data preprocessing. categorize and carefully ...

4.1 Prediction, Classification and Clustering. The remainder of the paper is largely concerned with prediction, classification and clustering for large datasets. These are related problems. In ...

K-nearest neighbors - It determines the class of the data point through a majority voting principle. It means that a class label can assigned to a data point based on it’s distance to it’s nearest ...

The prediction model is built with a data mining method it makes use of detailed employee information like age, years of experience, gender, marital status, department, and tenure. The datasets that ...