The research paper tries to spatially analyze various aspects of child mortality rates across India, divided into provinces and union territories. The study includes various visualizations, different tests, and finally, the building of multiple models/algorithms on the dataset gathered from the National Family Health Survey (NFHS-5), 2019-21 report.

The aim of the study is to find some patterns among the people, who suffer from obesity, related to their diet and the general lifestyle they follow. The analysis was carried out using the "ggplot2" library.

The study tries to build regression models for the dataset regarding various socio-economic factors including human life index and life expectancy for various countries. The conclusion of the whole analysis is to suggest which modeling technique would be the best for the given dataset, based on the RMSE metric for all these models.

The article involves building and fitting models for the dataset on the Bankruptcy of organizations. In total, 4 different models have been used including techniques to overcome the over-fitting issues. Moreover, feature selection was performed extensively to make sure the smooth execution of the whole analysis.

The article discusses various clustering techniques on a dataset containing various socio-economic factors and tries to cluster the countries in appropriate clusters. Moreover, it presents the results of performing dimension reduction techniques on the same dataset.

This paper explains everything from the need to do such analysis to the outputs of performing various classification models