Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of ...

Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program: Identify the core functionalities of data modeling in the data mining ...

Various data mining techniques, such as classification, clustering, and predictive analysis, help in transforming raw data into actionable intelligence.

Brief Description of Course Content Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to ...

Prediction – Prediction is a data mining technique that is often used in combination with other data mining techniques. It involves analyzing trends, classification, pattern matching, and relation.

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete ...

Predictive analytics, pattern recognition, and classification problems are not new. Long used in the financial services and insurance industries, predictive analytics is about using statistics, data ...

Aim of the Conference The MLDM´2018 conference is the fourteenth event in a series of Machine Learning and Data Mining meetings, initially organised as international workshops. The aim of MLDM is ...