Applying dimension reduction, clustering, classification, and regression techniques in R programming to analyze airline passenger satisfaction data. Identify the factors that significantly impact ...

However, these models face challenges in multiclass settings. A common solution is to transform the multiclass comparison into multiple two-class comparisons, which, while more effective than a global ...

For modeling this multi-label text classification approach, a corpus of beginner problems from a Brazilian OJ was manually curated using predefined class labels related to an introductory programming ...

Statistical modeling is an important aspect of data analysis that provides insights into complex datasets. R is an open-source programming language for statistical computing that offers an extensive ...

As the impact of Machine Learning (ML) on busi-ness and society grows, there is a need for making opaque ML models transparent and interpretable, especially in the light of fairness, bias, and ...

This article presents an analysis of a dataset related to slope stability circular failure cases using the GeneXproTools program. Two models were developed: The first model was utilized to find a ...

Various classification models are used in order to predict the dataset as a small Project to demonstrate R-Programming Skills. - oshinpojta/UCI---Dataset-Prediction-using-R ...