thesis.qmd

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title: "Thesis"
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For my thesis, I contributed new functionality to the `tidyclust` package in `R`. 
The `tidyclust` package exists as a part of the `tidymodels` framework , which 
follows the principles of the `tidyverse` to establish a consistent and 
reproducible workflow for unsupervised learning algorithms. My work adapted the 
Apriori and ECLAT algorithms for frequent itemset mining. This involved 
establishing a cluster assignment strategy that groups items based on frequent 
itemsets and support values, as well as a standardized methodology for 
predicting missing items. You can read more about my design choices in my paper 
or see them in my presentation!

[Thesis Paper - Frequent Itemset Mining with tidyclust in R](https://digitalcommons.calpoly.edu/theses/3019/){target="_blank"}

[Thesis Code - tidyclust Package](https://github.com/Wander03/tidyclust){target="_blank"}

[Thesis Presentation](files/thesis_presentation.pdf){target="_blank"}