| name | KSB-D07-K0022 |
| description | Machine Learning Applications: Clustering algorithms, classification methods, time series analysis, ensemble modeling techniques... |
| version | 1.0.0 |
| domain | D07 |
| domain_name | Spontaneous Reporting Systems |
| type | Knowledge |
| proficiency_level | L1 |
| bloom_level | understand |
| triggers | ["explain machine learning applications","what is machine learning applications","explain machine learning applications"] |
| epa_mapping | EPA-02, EPA-04, EPA-05 |
| cpa_mapping | CPA-02, CPA-05 |
| regulatory_refs | FDA-CFR-002, ICH-E2C(R2), ICH-E2F, EMA-GVP-004 |
KSB-D07-K0022: Machine Learning Applications
Overview
Domain: D07 - Spontaneous Reporting Systems
Type: Knowledge
Proficiency Level: L1 (Novice - Direct supervision required)
Bloom Level: Understand
Description
Clustering algorithms, classification methods, time series analysis, ensemble modeling techniques
Context
- Major Section: Global Spontaneous Reporting System Architecture
- Section: Intelligent Analytics and Pattern Recognition
EPA Mapping
- EPA-02:3004-3005
- EPA-04:3009-3010
- EPA-05:3011-3012
CPA Pathway
Regulatory References
- FDA-CFR-002
- ICH-E2C(R2)
- ICH-E2F
- EMA-GVP-004
Instructions
When this skill is activated, Claude should:
- Demonstrate L1 proficiency in machine learning applications
- Apply understand level cognitive skills to explain the topic
- Reference relevant regulatory guidance (FDA-CFR-002, ICH-E2C(R2), ICH-E2F, EMA-GVP-004)
- Connect to related EPAs: EPA-02, EPA-04, EPA-05
Key Competencies
- Clustering algorithms, classification methods, time series analysis, ensemble modeling techniques
Assessment Criteria
- Can explain core concepts independently
- Demonstrates understanding of regulatory context
- Applies knowledge appropriately to PV scenarios
Related Skills
- Other D07 skills in Intelligent Analytics and Pattern Recognition
- Cross-domain integrations per DAG architecture
Generated from PV KSB Framework v1.0 | 2025-12-31
