Speed dating is a relative new concept that allows researchers to study various theories related to mate selection. A problem with current research is that it focuses on finding general trends and relationships between the attributes. This report explores the use of machine learning techniques to predict whether an individual will want to meet his partner again after the 4-minute meeting based on their attributes that were known before they met. We will examine whether Random Forest or Extremely Randomized Trees perform better than Support Vector Machines for both limited attributes describe appearance only and extended attributes includes answers to some questions about their preferences.
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