Classification of T lymphocyte motility behaviors using a machine learning approach
Fig 5
Performance evaluation of the classifier trained on the Astro A dataset and tested on the Astro B dataset.
Performance evaluation of the model for classifying synapse vs. kinapse-like behaviors (A, B) and dancing, scanning, and poking visually identified behaviors (C, D) using the Astro A dataset for training and validation and the Astro B dataset for testing. A, C) Average cross-validation (CV) accuracy according to the number of features included in the analysis. The doted lines represent the minimal and maximal values. The test set accuracy on the Astro B dataset is indicated as a red square for the number of features selected for the final classifier. B, D) Confusion matrices illustrating the predicted values in the Astro B dataset using the classifier trained on the Astro A dataset for each behavior either synapse vs. kinapse (B) or dancing, scanning, and poking (D).