Machine Learning Algorithm Comparison

Algorithms were compared on OpenML datasets. There were 19 datasets with binary-classification,
7 datasets with multi-class classification, and 16 datasets with regression tasks. Algorithms were trained with AutoML mljar-supervised. They were trained with advanced feature engineering switched off, without ensembling. All models were trained with the 5-fold cross validation with shuffle and stratification (for classification tasks). Different hyperparameters (if available) for each algorithm were checked during the training.

For binary and multi-class classification the Accuracy metric was used. The regression task was optimized with Root Mean Square Error.