Computing Intra-Class and Inter-Class Distances

MATLAB 803B 292 views 0 downloads 1 credits
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Resource Overview

Iterate through files in a directory and calculate intra-class distances (within-class variation) and inter-class distances (between-class separation) with code implementation details.

Detailed Documentation

In this task, we need to traverse files within a directory, identify all data files, and load their contents. We then compute distances between data points within each file to determine intra-class distances, typically using distance metrics like Euclidean or Manhattan distance implemented through vectorized operations. Next, we calculate distances between different categories to obtain inter-class distances, which may involve comparing class centroids or employing statistical measures like Bhattacharyya distance. These calculations help us better understand data distribution characteristics and establish a foundation for subsequent analysis such as clustering evaluation or classification model validation. Key implementation steps include file parsing using OS module functions, distance matrix computation with NumPy broadcasting, and aggregation methods for statistical summaries.

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