My CVProjects
In this section, you’ll find a collection of my work in machine learning, statistical modeling, and data analysis, ranging from predictive solutions (e.g., League of Legends win prediction) to robust models for complex scenarios (e.g., zero-adjusted inverse gamma regression). Each project blends methodological rigor, creativity, and real-world application, reflecting my passion for statistics and the data universe.
Gradient Boosting Machine Comparative
Comparative analysis of various Gradient Boosting Machine (GBM) models applied to diverse datasets, evaluating their performance across different scenarios. Our study focused on assessing each model's efficiency in handling both regression and classification tasks, with particular emphasis on large-scale datasets and non-numerical features.
View Full AnalysisPrincipal Component Analysis and Hierarchical Clustering for Glass Type Identification
The goal of this work is to explore the Glass Identification dataset using these two multivariate techniques. Principal Component Analysis (PCA) was used to reduce the dataset's dimensionality and facilitate pattern visualization, while Cluster Analysis was applied to identify potential glass groups related to their categories. The application of these techniques not only demonstrates their usefulness in analytical contexts but also highlights how statistical tools can be applied in practical fields, such as forensic science.
View Full StudyChat with Me
May 2025: I have set up the online-coffee-time (Inspired by Shangzhe Wu). Welcome to chat with me!