I have a question on the part 2 tutorial on the bear detector. I followed the steps pretty much step by step but substituted duck duck go for the bing search utility to get my bears. When I get to the plot_confustion_matrix step, I expected to get numbers bigger than what I get in the matrix. Despite having downloaded about 90 bear images, I get numbers in the matrix that don’t add up to anywhere close to 90. What I get is 4, 5, and 6 in the diagonal (correct identifications) for black, grizzly and teddy bears respectively. Any idea on what is going on here?
I need more information on your code to be more helpful. It will be best if you can share the notebook or paste the code here.
From what I know, plotting confusion matrices sometimes show erratic data when used on kaggle, I don’t know which platform you’re using, but at least try switch to google colab or your local environemnt and try again.
Thanks Jumpy Jason, I was thinking chapters vs. parts (re. Part 1 2022 Topic). I am using Kaggle, but I will try in Google Colab first before reposting.
Thanks!
Hello @tbyrondouglas,
It sounds like your dataset wasn’t properly labeled or loaded—DuckDuckGo may have returned fewer usable or correctly classified images than expected. Double-check your image folder structure and ensure each class is correctly mapped. Also verify your validation set size; the confusion matrix only reflects predictions on that subset, not the full 90 images.