Personality Prediction Project With ML and Python

Published on 14 May 2022. Written by Avantika Dhar

Human beings tend to learn from previous experiences. The same thing is done nowadays digitally, and the technology is known as Machine Learning. Machine Learning is a branch of Artificial Intelligence or in short AI, the hot cake of today’s technology. Using Machine Learning we can do a lot of stuff, for instance, predicting Bitcoin prices, movie ticket price prediction or people you may know the section on Facebook. Even ML Is used in medical science also. Nowadays, researchers are also able to predict personality using Machine Learning.

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SLNOTE


Concepts Used:

• Python Programming Language (Python 3 or above)

• Some basic machine learning algorithms

Hardware and Software Used:

• Operating system that you prefer (it could be Linux, Mac or Windows)

• A PC or laptop that you own

• Your PC or laptop should have enough RAM to run the calculations uninterruptedly. 

• Python 3 or above installed in your system.

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What Are The ‘5 Personality Factors’?

The 5 personality factors are Neuroticism, Extraversion, Openness to experience, agreeableness, conciseness. 

Implementations:

1. Download the dataset from myPersonality. Split the dataset into two parts. The dataset consists of data from 700,000 Facebook users with over 10,000 above statuses. These data will help you to predict the personality of a person.
2. Personality can be described by 5 personality factors and this can predict the views and behaviour of a person.
3. When a user has near about 100 likes in sports and 20 likes in politics, it is obvious that the person is definitely interested in sports than politics. This means his 5% interest is in politics. This value will improve the value of our RMSE results by 5%. We will put this data under Result column. 
4. Here we have used Random Forest classification algorithm. 
5. Now we have to create the decision tree. To do so we need to map the data in n-dimensional space. Each space stands for one like. 
6. Random Forest algorithm then decides boundary and divides the dataset into two parts that overlap each other.
7. Now the big 5 Personality factors are placed on linear line and are predicated on a basis of 1-5 points. Linear Regression is another learning technique (algorithm). This creates a model based on a numeric value that has more than one features.
8. Calculate the RMSE to predict and calculate the performance of the model you have just created. If the value is closer to zero, the better and accurate the model is.
9. For this project, always choose an algorithm that is efficient in calculating continuous values.

Conclusion:

This prediction is almost 8-15% close to the original personality trait a person has. To predict the personality of a person, social media websites play a vital role. We have used the Facebook API to train our model and also to make the calculations more accurate.

SLDYK
Kit required to develop Personality Prediction Project With ML and Python:

• Python

Technologies you will learn by working on Personality Prediction Project With ML and Python:

• Machine Learning

Any Questions?