Guest Lecture on "Data Mining"
Department of MCA has conducted a Guest Lecture on
"Data Mining" by
Guest Lecture has been organized in two sessions(morning and afternoon).
In the morning Session the following concepts are discussed :
- Top Ten Recent Innovations
- Challenges in DM
- Developing a Unifying Theory of Data Mining
- Scaling Up for High Dimensional Data and High Speed Streams
- Sequential and Time Series Data
- Mining Complex Knowledge from Complex Data
- Data Mining in a Network Setting
- Distributed Data Mining and Mining Multi-agent Data
- Data Mining for Biological and Environmental Problems
- Data-mining-Process Related Problems
- Security, Privacy and Data Integrity
- Dealing with Non-static, Unbalanced and Cost-sensitive Data
In the Afternoon Session the following concepts are discussed :
- Top 18 DM Algorithms
- Top Ten Algorithms in DM
- C4.5 and Beyond
- The K-Means Algorithm
- Support Vector Machines
- The Apriori Algorithm
- The EM Algorithm
- Page rank
- AdaBoost
- KNN: K-Nearest Neighbor Classification
- Naive Bayes
- CART
