The Evolutionary Enhancement in the technology Innovation, Fast Processing Procedures
and Networking systems encouraged the Business organizations to gather and store large …

Education infrastructure is one of the main barriers on school quality in Low-and Middle-
Income Countries (L&MICs), since it is insufficient and unevenly distributed. Improving the …

Categorical data clustering is a difficult and challenging task due to the special characteristic
of categorical attributes: no natural order. Thus, this study aims to propose a two-stage …

Clustering and classification are two important techniques of data mining. Classification is a
supervised learning problem of assigning an object to one of several pre-defined categories …

Clustering is a well-established unsupervised data mining approach that group data points
based on similarities. Clustering entities will give insights into the characteristics of different …

In this research, k-means, agglomerative hierarchical clustering and regression analysis
have been applied in hydrological real time series in the form of patterns and models, which …

This paper presents a review of runoff forecasting method based on hydrological time series
data mining. Researchers are developed models for runoff forecasting using the data mining …

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the
classification of land cover, such as forest canopies, vegetation, sea ice types, and urban …

Learning is the process of generating useful information from a huge volume of data.
Learning can be either supervised learning (eg classification) or unsupervised learning (eg …

Some clustering algorithms calculate connectivity of each data point to its cluster by
depending on density reachability. These algorithms can find arbitrarily shaped clusters, but …