Hi Shravanthi,
I understand that you have used Radial Basis Function (RBF) network for image classification and you want to know how to evaluate your detector.
To determine if your trained RBF network has correctly recognized images, start by evaluating its accuracy using a confusion matrix, which highlights correct and incorrect classifications for each class, and calculating the overall accuracy. For more nuanced insights, especially in cases of class imbalance, assess the network’s precision, recall, and F1-score, which respectively measure the accuracy of positive predictions, the model’s ability to capture all relevant instances, and the balance between precision and recall. For binary classifications, you can also use the ROC curve and its Area Under the Curve (AUC) to understand the model’s performance at various thresholds.
Please go through the following example to learn more on how to evaluate a image classifier,
Also please go through the following documentation to learn more regarding how to properly post in MATLAB answer to get quick reply,
Hope this helps.
