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 ...

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 data ...

The second step in data mining process is the application of various modeling techniques. These are used to calibrate the parameters to optimal values. Techniques employed largely depend on analytic ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...

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 ...

Predictive analytics enables you to develop mathematical models to help you better understand the variables driving success. Predictive analytics relies on formulas that compare past successes and ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

July 14th - 19, 2018 New York, USA Chair: Prof. Dr. Petra Perner Institute of Computer Vision and applied Computer Sciences, IBaI Leipzig/Germany Tutorials Data ...