Introduction When faced with a small dataset in machine learning, the selection of an appropriate model is crucial for achieving optimal performance. This analysis delves into the comparative effectiveness of Logistic Regression, Support Vector Machines (SVM), and Random Forest algorithms when applied to limited data scenarios, drawing insights from the provided source material (https://machinelearningmastery.com/logistic-vs-svm-vs-random-forest-which-one-wins-for-small-datasets/). The…