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Hey...I became really interested in your code for plant diseases detection that was included in your CropCare ai project.
I wanted to integrate that AI into my website. I found out that the AI had some problems running in the older version of sklearn. So I decided to fine tune it using the newer version of sklearn. So as I was reading through your code in the notebook.I saw that you had achieved a 99.2% accuracy on the training samples. Isn't that overfitting?. I wanted to know how can I reduce the accuracy of the model to make it more adaptable AI. Do I wanna change the modelling or shouldni change the architecture.
I'll be looking forward for your reply and guidance on this issue
The text was updated successfully, but these errors were encountered:
Hello....It's Musthafa on this side
Hey...I became really interested in your code for plant diseases detection that was included in your CropCare ai project.
I wanted to integrate that AI into my website. I found out that the AI had some problems running in the older version of sklearn. So I decided to fine tune it using the newer version of sklearn. So as I was reading through your code in the notebook.I saw that you had achieved a 99.2% accuracy on the training samples. Isn't that overfitting?. I wanted to know how can I reduce the accuracy of the model to make it more adaptable AI. Do I wanna change the modelling or shouldni change the architecture.
I'll be looking forward for your reply and guidance on this issue
The text was updated successfully, but these errors were encountered: