Question on confusion matrix on optimized parameters (100% accuracy)

Greetings everyone!

I have question related to the confusion matrix based on selecting the best parameter. The first image is the entire workflow to date which shows a phase by which I conduct a grid search on hyper parameters with the goal of using the best return for the final model. As shown below, the best hyper parameter combination gave me the following confusion matrix together with a 92% accuracy and other stellar classification-based statistics

However, when I go to use the chosen parameters established on the “Using best parameters” phase to the “Using best parameters” phase, I get the following confusion matrix together with a suspect 100% accuracy, rather than something that resembles the statistics established in the first step. I am optimizing to maximize accuracy.

Im wondering what might be the case and how I can fix this issue.

Thank you again everyone for helping me learn the ropes related to data science and machine learning. I look forward to continue this process. You all have been great thus far! :slight_smile:

~Cole K.