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 ...

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 ...

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 ...

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 ...

*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.

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 ...