Experiment on the performance of different machine learning algorithms for classification - Results

Results of a short performance study of machine learning algorithms Context and methodology This data was produced while performing a university project to examine the performance of various machine learning algorithms on different prediction datasets The data serves the purpose of comparing the metrics of performing the different tasks The dataset contains a number of matrices for every classifier and every dataset The data was produced with python scripts provided further down and with the usage of the external datasets: Membership Woes Dataset (OpenML): https://api.openml.org/d/44224 Zoo dataset (UCI): https://doi.org/10.24432/C5R59V Breast Cancer Dataset: https://github.com/moritx/performance-experiment-machine-learning/tree/main/data Loan Dataset: https://github.com/moritx/performance-experiment-machine-learning/tree/main/data Technical details The data consists of one JSON file The source code for producing this data is available at https://doi.org/10.5281/zenodo.11085222 Structure of the data [ {"classifier": ...,"dataset": ...,"hyper_parameters": ...,"cross_validation_results": { "fit_time": {} , "score_time": ..., "metrics": {}}, "holdout_test_results": ...}, ]