This jupyter notebook project was completed by me and my friend using the dataset from Kaggle.
The world Happiness 2017, which ranks 155 countries by their Happiness Levels was released at the UN
at an event celebrating International Day of Happiness on March 20th. The dataset in this lists happiness levels of people in those 155 countries.
We are using Association Rule Mining to find out what factor or feature is the most important in deciding the happiness levels.
The following shows the steps carried out in the Jupyter notebook:
- The Jupyter notebook starts by reading the csv file
- Data Cleaning
- Making Histogram and Box Plots
- Testing for Redundancies using Chi-Square Test
- Checks Correlation between attributes
- Dimensionality Reduction using PCA
- Generating Features by first dividing data into two categories
- Generating and Analyzing rules using Apriori