Using K-means and Agglomerative clustering, the used vehicle data is segmented based on certain factors. Both quadratic and linear discrinant analysis as well as logistic regression is also carried out on the data.
The Dataset provided shows different variables/properties which buyers generally consider before purchasing a fairly used car. Some of these variables covered the mileage of each vehicle, the make/model and the fuel type, which are all the predictor variables whilst Price is the dependent variable.
For a proper analysis, the data was wrangled and cleaned thoroughly using python. The next step was to carry out clustering/grouping analysis using KMeans clustering. Agglomerative Clustering was also carried out, as well as logistic Discriminant Analysis and Quadratic Discriminant Analysis.