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Unsupervised learning coupled with applied factor analysis to the five-factor model (FFM), a taxonomy for personality traits used to describe the human personality and psyche, via descriptors of common language and not on neuropsychological experiments. Used kmeans clustering and feature scaling (min-max normalization).

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About

The Big Five personality traits, also known as the five-factor model (FFM) and the OCEAN model, is a taxonomy, or grouping, for personality traits. When factor analysis (a statistical technique) is applied to personality survey data, some words used to describe aspects of personality are often applied to the same person. For example, someone described as conscientious is more likely to be described as "always prepared" rather than "messy". This theory is based therefore on the association between words but not on neuropsychological experiments. This theory uses descriptors of common language and therefore suggests five broad dimensions commonly used to describe the human personality and psyche. (wikipedia)

Dataset

  • The [IPIP-FFM-data-8Nov2018] Dataset -- This dataset contains 1,015,342 questionnaire answers collected online by Open-Source Psychometrics Project.

Techniques Used

  • Mini Batch K-means algorithm
  • Min-Max Normalization

Applications

  • Jupyter Notebook
  • Anaconda

Libraries

  • Pandas (Python Data Analysis Library)
  • Matplotlib
  • Numpy

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About

Unsupervised learning coupled with applied factor analysis to the five-factor model (FFM), a taxonomy for personality traits used to describe the human personality and psyche, via descriptors of common language and not on neuropsychological experiments. Used kmeans clustering and feature scaling (min-max normalization).

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