Fig. 4
From: DREAMER: a computational framework to evaluate readiness of datasets for machine learning
DREAMER framework evaluation across multiple datasets. a Comparison of raw and cleansed data quality scores for the FHS dataset, illustrating the impact of DREAMER’s data cleansing. b Comparison of classification and clustering accuracies between raw and cleansed data for the FHS dataset, providing insights into the impact of data cleansing on these metrics. c Comparison of raw and cleansed data quality scores for the ADNI dataset, illustrating the impact of DREAMER’s data cleansing. d Comparison of classification and clustering accuracies between raw and cleansed data for the ADNI dataset, providing insights into the impact of data cleansing on these metrics. e Comparison of raw and cleansed data quality scores for the WDBC dataset, illustrating the impact of DREAMER’s data cleansing. f Comparison of classification and clustering accuracies between raw and cleansed data for the WDBC dataset, providing insights into the impact of data cleansing on these metrics