Data Mining Based on Condensed Hierarchical Clustering Algorithm

Clustering is an important part of data mining, which aims to divide unknown sample data into multiple classes according to similarity relationship. According to the characteristics of multi-subject high-dimension of training data, this paper preprocesses the training data by linear dimensionality reduction and analyzes the training data based on condensed hierarchical clustering algorithm. From the perspective of practical application, this clustering analysis method of training data effectively differentiates personnel reasonably and intuitively reflects the performance characteristics of various types of personnel, providing scientific guidance for the development and implementation of training plans.