This homework focuses on tuning and evaluating nonlinear regression models using both simulated and real-world datasets. We explore the impact of variable correlation on feature importance (8.1–8.3), investigate bias in tree-based models (8.4–8.6), and finally apply model tuning techniques to the Chemical Manufacturing Process dataset (8.7). Across the exercises, we rely heavily on the caret framework for resampling, model training, and performance evaluation. Techniques like bagging, boosting, and SVMs are compared using RMSE and R² to identify the most effective approach. Along the way, we also evaluate how model interpretation changes when predictors are duplicated or correlated.

This is a horizontal bar graph depicting law enforcement staffing, filtering for Group I (85 cities, 250,000 and over; population 62,520,440). The Y-axis is labeled with U.S regions, and the X-axis is labeled with the number of officers serving in these cities. The northeast region dominates the graph.

PCA on the World Happiness Report 2019 https://worldhappiness.report/ed/2019/

ISLR Chapter 7 - Questions 6 and 10

Código para rascado web para la propuesta de investigación realizada por Montserrat Villarreal sobre populismo y cortinas de humo

This report analyzes spending trends in selected U.S. federal budget categories from fiscal year 2000 through estimated 2025 figures. The analysis focuses on categories such as International Affairs, Science, Energy, Environment, Agriculture, Commerce, Transportation, Community Development, and Veterans Benefits. These categories make up a sliver of the entire government's budget compared with health insurance (Medicare and Medicaid), Social Security and defense spending.