P. G. Lovaglio

An Integrated Gradient Boosting Machine Approach With Fisher's Discriminant Analysis: Empirical Assessment on Five Benchmark Datasets and Simulations

The aim of this study is to assess the impact of different dimensionality reduction techniques—specifically Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (LDA)—on the classification performance of Gradient Boosting Machines (GBM). While PCA is commonly employed to reduce feature dimensi...