Answer
See the explanation
Work Step by Step
- **Cluster Analysis:** Cluster analysis is a method used in data mining and statistics to classify a set of objects into groups (or clusters) so that objects in the same group are more similar to each other than to those in other groups. It helps to identify patterns and structures within data by grouping similar data points together.
- **Association Analysis:** Association analysis, also known as market basket analysis, is a technique used to discover relationships between variables in large datasets. It identifies associations or correlations among different variables, often used in retail for understanding customer purchasing behavior or in healthcare for identifying disease co-occurrences.
- **Outlier Analysis:** Outlier analysis involves identifying and examining data points that deviate significantly from the rest of the data in a dataset. Outliers can represent errors, anomalies, or rare events, and analyzing them can provide insights into the underlying data distribution or reveal important patterns that might otherwise be obscured.
- **Sequential Pattern Analysis:** Sequential pattern analysis is a data mining technique used to discover patterns or sequences of events over time in a dataset. It is often applied in areas such as web usage mining, where the order of events or actions matters, and the goal is to uncover meaningful sequences or temporal dependencies within the data.
