| _version_ | 1866902087652081664 |
|---|---|
| author | Di Rienzo, Mirco |
| author_facet | Di Rienzo, Mirco |
| contents | <p>This app allows you to perform regression on images containing graph trends, using various fitting methods; approximate an equation for the chosen method; and make predictions. It is divided into three modules:</p> <ul> <li> <p><strong>Module A</strong><br>You can upload and edit an image, set editing and analysis parameters, run regressions or clustering, and then export the resulting data.</p> </li> <li> <p><strong>Module B</strong><br>You train a model using the CSV files generated in Module A. This module also performs statistical analysis on the scatterplot points to identify statistical outliers via a z-score and p-value on the principal features that defined the classes.</p> </li> <li> <p><strong>Module C</strong><br>You automatically generate CSVs from multiple images by either loading a reference CSV of analysis parameters or by using the sidebar (which is itself divided into submodules). Within Module C, you choose whether to reinforce the model trained manually in Module B or to classify using the current (unsupervised) model. Finally, you can select the incorrect predictions and calculate the model’s overall accuracy.</p> </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15836412 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Regressor Classifier from images, url app, you tube link Di Rienzo, Mirco AI, MACHINE LEARNING MODEL, REGRESSOR, CLASSIFIER <p>This app allows you to perform regression on images containing graph trends, using various fitting methods; approximate an equation for the chosen method; and make predictions. It is divided into three modules:</p> <ul> <li> <p><strong>Module A</strong><br>You can upload and edit an image, set editing and analysis parameters, run regressions or clustering, and then export the resulting data.</p> </li> <li> <p><strong>Module B</strong><br>You train a model using the CSV files generated in Module A. This module also performs statistical analysis on the scatterplot points to identify statistical outliers via a z-score and p-value on the principal features that defined the classes.</p> </li> <li> <p><strong>Module C</strong><br>You automatically generate CSVs from multiple images by either loading a reference CSV of analysis parameters or by using the sidebar (which is itself divided into submodules). Within Module C, you choose whether to reinforce the model trained manually in Module B or to classify using the current (unsupervised) model. Finally, you can select the incorrect predictions and calculate the model’s overall accuracy.</p> </li> </ul> |
| title | Regressor Classifier from images, url app, you tube link |
| topic | AI, MACHINE LEARNING MODEL, REGRESSOR, CLASSIFIER |
| url | https://doi.org/10.5281/zenodo.15836412 |