It all depends on the data variability.
If the time series are too variable between each other in terms of raw values, you might not see any meaningful cluster.
That's why you will want to transform the data to make the times series more comparable.
A first step would be to have relative values instead of absolute values if you want to detect behavioral ...
The author is right. Data Leakage is when you used additional information not available during training for training your ML model. In PCA if you use test data you are using some insights from test data as part of your training process hence data leakage.
Machine learning mastery explains data leakage as below :
Data leakage can cause you to create overly ...