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 ...

This R Markdown project performs predictive modeling for glioma grading (LGG vs. GBM) using clinical and molecular features, comparing k-NN, Naive Bayes, and Decision Tree models.

Learn how to use R, a popular language for data analysis and statistics, for text classification in four steps: loading and preprocessing the data, creating and training the model, evaluating the ...

Image classification is an important Machine Learning task which assigns a label to an input image. It is quite a common practice among ML enthusiasts to implement the task of classifying images using ...

Enot, D., Lin, W., Beckmann, M. et al. Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data.

This is a full paper, and it belongs to the research category. Online Judges (OJs) have been used by students and programming practitioners to solve problems by submitting solutions as source code and ...

Jeffrey Parsons, Yair Wand, Using Cognitive Principles to Guide Classification in Information Systems Modeling, MIS Quarterly, Vol. 32, No. 4 (Dec., 2008), pp. 839-868 ...

Genetic programming (GP) has emerged as a potent evolutionary methodology for autonomously designing image classifiers and extracting relevant features. Its capacity to evolve interpretable models ...

In this paper, we address this problem by extracting interpretable, transparent models from opaque ones via a new readability-enhanced multi-objective Genetic Programming approach called REMO-GP. To ...