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": ...}, ]