Date of Award
8-2023
Document Type
Thesis
Degree Name
Master of Historic Preservation (MHP)
Department
Historic Preservation
Committee Chair/Advisor
Dr. Jon Marcoux
Committee Member
Richard Marks
Committee Member
Dr. Jeffrey E Klee
Committee Member
Dr. Aric LaBarr
Abstract
Since the passing of the National Historic Preservation Act in 1966, the realm of architectural history has evolved, becoming more interdisciplinary. There was a shift in focus from looking at architecture from a fine art point of view to looking at it through a social lens. The new social perspective approach focused not only on the buildings but also on the people that inhabited or constructed the space. Approaching architectural investigations in this manner has allowed for a deeper understanding of the influences that shaped the built environment. Advancements in technology have also aided in furthering our overall comprehension of the human landscape. Methods such as paint analysis and dendrochronology allow for more complete interpretations and more accurate dating practices.
The purpose of this thesis is to continue the multidisciplinary evolution that has been occurring since the 1960s by blending data analysis and architectural history through the use of logistic regression. By employing logistic regression, this study aims to show the predictive power this method has regarding identification and classification. Using quantitative measurements from 210 different unique door architraves, the logistic regression model identified seven key variables that helped classify Georgian and non-Georgian architraves with a high accuracy rate. The results from the model also helped identify some stylistic changes that occurred over time and some elements that had continuity, opening a discussion of what this said about the people designing and constructing these architectural details.
Recommended Citation
Pilcher, Chase, "Quantitative Techniques for Classifying Mouldings: An Exploration of Logistic Regression within Architectural Investigations" (2023). All Theses. 4083.
https://tigerprints.clemson.edu/all_theses/4083