In PCA technique, we scale the the training and test data simultaneously. Now to scale the unseen/prediction dataset, do we need to use the same scale i.e. (same mean and standard deviation) as used in the training and the test dataset or we can scale the unseen/prediction data on its own scale.
You have to scale using the training set only. The test set and any other future data should never be included in the construction of the scaling. This will lead to snooping and potentially overfitting.