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Tarikere Shivaprasad, Priyadarshini (2018) Machine Learning Approaches To Identify Preferences In An Ideal Match Using Speed Dating Data. Masters thesis, Dublin, National College of Ireland.
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Abstract
Speed dating data has various angles to look at. It is a 4-minute conversation between two people to find a desirable match. In this research, an analysis on attributes that influence a participant's decision on further contact is examined. The data is also explored in terms of gender preferences, hobbies and change in self perception over time. Machine learning algorithms like Naïve Bayes, Random Forest, C5.0 and Gradient Boosted Decision Tree are used to determine the predominant attributes on decision making. Exploratory analysis was done on self-perception. Multiple regression was implemented to analyze a match with socio-cultural attributes. Gradient boosted decision tree performed better with an accuracy of 75.74 percent compared to other implemented classifiers. Attractiveness and fun stands out as desirable attributes in a prospective match.
| Item Type: | Thesis (Masters) |
|---|---|
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Caoimhe Ní Mhaicín |
| Date Deposited: | 03 Nov 2018 12:59 |
| Last Modified: | 03 Nov 2018 13:01 |
| URI: | https://norma.ncirl.ie/id/eprint/3417 |
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