# Train your classifier for multiple fruits and vegetables ## Instructions In this lesson, you trained an image classifier to distinguish between ripe and unripe fruits, but only for one type of fruit. A classifier can also be trained to recognize multiple fruits, though its success may vary depending on the type of fruit and the differences between ripe and unripe stages. For instance, for fruits that change color as they ripen, image classifiers might be less effective than a color sensor, as they typically work with grayscale images rather than full-color ones. Try training your classifier with other fruits to evaluate its performance, especially when the fruits look similar. For example, apples and tomatoes. ## Rubric | Criteria | Exemplary | Adequate | Needs Improvement | | -------- | --------- | -------- | ----------------- | | Train the classifier for multiple fruits | Successfully trained the classifier for multiple fruits | Successfully trained the classifier for one additional fruit | Unable to train the classifier for more fruits | | Determine how well the classifier works | Correctly commented on how well the classifier performed with different fruits | Observed and provided suggestions on how well it worked | Unable to comment on the classifier's performance | --- **Disclaimer**: This document has been translated using the AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). While we aim for accuracy, please note that automated translations may include errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is advised. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.