PRACTICAL_LIST

Practical 1: Data Domain selection and Identification of Characteristics of selected Dataset of different formats

Practical 2: Data Preprocessing For selected dataset generate Five Number Summary using Python. Also generate mode and midrange. Implement data smoothing and data normalization methods. Redundancy analysis using Pearson correlation and Chi- Square. Discretization by Intuitive Partitioning.

Practical 3: OLAP Operation and Analysis Creating Data Cube and Performing OLAP Operations for selected Dataset.

Practical 4: Data Analysis Apply Classification and Clustering Techniques for selected datasets.

Practical 5: Pattern Analysis

• Implementation of various classification and regression techniques.
• Implement Association Rule Mining using different algorithms.

source: list-of-practicals