it's always important to approach any claim of 100% accuracy with a critical eye. Achieving 100% accuracy is nearly impossible in any practical dataset, and it is usually an indication of overfitting or other statistical biases in the model.

It is also essential to examine the data transformation and feature selection process used in the model as these can have a significant impact on model performance and biases. It's important to ensure that these processes are transparent, unbiased, and validated using appropriate statistical methods.