clear up confusing error message for non-contiguous labels in rf classifier [skip-ci]

[eordentlich]

• add docstring note about this requirement

[greptile-apps]

Greptile Overview

Greptile Summary

Improved error messaging for RandomForestClassifier when GPU workers don't receive all required label values. The changes consolidate duplicate error messages and provide clearer guidance on workarounds, while adding comprehensive docstring documentation about the label requirements.

Key Changes

• Consolidated error messages into a single, reusable string variable in tree.py:416-418
• Updated error message to explicitly state the requirement for labels in range 0, 1, ..., num_classes - 1
• Added detailed docstring notes in classification.py:421-426 explaining label requirements and workarounds
• Error messages now provide actionable workarounds: remap labels, increase rare label occurrences, reduce workers, or shuffle input data
• Removed redundant error message text from two locations in the code

Confidence Score: 5/5

• This PR is safe to merge with minimal risk
• The changes are purely documentation and error message improvements without any logic modifications. The error handling paths remain identical, only the message text is improved for clarity and consolidated for maintainability. No behavioral changes are introduced.
• No files require special attention

Important Files Changed

File Analysis

Filename	Score	Overview
python/src/spark_rapids_ml/classification.py	5/5	Added docstring notes clarifying label requirements for RandomForestClassifier
python/src/spark_rapids_ml/tree.py	5/5	Improved error messages for missing label values with actionable workarounds

Sequence Diagram

sequenceDiagram
    participant User
    participant RandomForestClassifier
    participant Worker as GPU Worker
    participant TreeLite
    
    User->>RandomForestClassifier: fit(data)
    RandomForestClassifier->>Worker: Distribute data across workers
    
    alt Classification Task
        Worker->>Worker: rf.fit(X, y)
        Worker->>Worker: Check if rf.classes_.max() != rf.n_classes_ - 1
        
        alt Missing Labels Detected
            Worker-->>User: RuntimeError: "A GPU worker did not receive all label values..."
        else All Labels Present
            Worker->>Worker: Serialize model
            Worker->>TreeLite: Create TreeLite models
            
            alt Worker 0 Concatenates Models
                TreeLite->>TreeLite: Model.concatenate(all_models)
                
                alt Concatenation Fails (different num_class)
                    TreeLite-->>User: RuntimeError: "A GPU worker did not receive all label values..."
                else Concatenation Succeeds
                    TreeLite->>RandomForestClassifier: Return final model
                    RandomForestClassifier->>User: Model trained successfully
                end
            end
        end
    end

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