In this project, a machine learning classification model has been developed and trained to predict the Myers–Briggs Type Indicator (MBTI) of a person, based on some questions.
A supervised machine learning classification model has been developed and trained on MBTI Dataset which attempts to predict the 16-way personality code as well as each binary character code along each axis.
The Myers Briggs Type Indicator (or MBTI for short) is a personality type system that divides everyone into 16 distinct personality types across 4 axis:
Introversion (I) — Extroversion (E) Intuition (N) — Sensing (S) Thinking (T) — Feeling (F) Judging (J) — Perceiving (P)
The purpose of this project is to investigate if any patterns can be detected in a person’s specific personality type in connection to their style of writing and to explore the validity of the test in analysing, predicting, or categorizing behaviour. The dataset contains ~8600 observations (people), where each observation gives a person’s: Myers-Briggs personality type (as a 4-letter code) - An excerpt containing the last 50 posts on their Personality Cafe forum (each entry separated by “|||”)
The overall goal for the outcome is to be able to predict a person’s personality type based on some text that they have written, as well as evaluate the validity of the MBTI’s test and its ability to predict the converse — using MBTIs to predict language styles and behaviour.