This repository contains the implementation of known formulas in the field of Data Mining / Machine Learning / Statistics using Python and the Numpy library.
Segmentation of the Statistics Canada’s Set of Proximity Measures – A Clustering Algorithm Approach. UBC MDS capstone project for Statistics Canada.
This Java project compares Linear, Binary, and HashSet Search algorithms, evaluating efficiency in large datasets. It also analyzes word proximity to uncover relationships and patterns. HashSet Search is fastest (6 ms), followed by Binary (14 ms), with Linear Search taking 3,229 ms.
Segmentation of the Statistics Canada’s Set of Proximity Measures – A Clustering Algorithm Approach. UBC MDS capstone project for Statistics Canada.
Comparsion of Partition Clustering Algorithm and Proximity Measure
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