text: Title: Extend label issue detection in Datalab to work even without pred_probs input
  Body: Goal: extend the label issue check in Datalab to work even if user only provided: `features`, `labels` to `Datalab.find_issues()`.
  
  There are multiple ways this can be achieved:
  
  Option 1 (easiest): Use sklearn `KNNclassifier` (or `LogisticRegression`) applied to `X=features, y=labels` in order to produce out-of-sample `pred_probs` and then continue as usual.
  
  Option 2: Use methods from other papers like these (requires benchmarking them first):
  - [SelfClean: A Self-Supervised Data Cleaning Strategy](https://arxiv.org/abs/2305.17048)
  - [Detecting Corrupted Labels Without Training a Model to Predict](https://arxiv.org/abs/2110.06283)
  
  