Learning Graph Quality Metrics Report¶
Overview¶
- Total Concepts: 200
- Foundational Concepts (no dependencies): 1
- Concepts with Dependencies: 199
- Average Dependencies per Concept: 1.45
Graph Structure Validation¶
- Valid DAG Structure: ✅ Yes
- Self-Dependencies: None detected ✅
- Cycles Detected: 0
Foundational Concepts¶
These concepts have no prerequisites:
- 1: Machine Learning
Dependency Chain Analysis¶
- Maximum Dependency Chain Length: 10
Longest Learning Path:¶
- Machine Learning (ID: 1)
- Supervised Learning (ID: 2)
- Neural Network (ID: 82)
- Artificial Neuron (ID: 83)
- Forward Propagation (ID: 92)
- Backpropagation (ID: 93)
- Gradient Descent (ID: 94)
- Optimizer (ID: 187)
- Momentum (ID: 190)
- Nesterov Momentum (ID: 191)
Orphaned Nodes Analysis¶
- Total Orphaned Nodes: 112
Concepts that are not prerequisites for any other concept:
- 12: Feature Vector
- 18: Euclidean Distance
- 19: Manhattan Distance
- 20: K Selection
- 22: Voronoi Diagram
- 24: KNN for Classification
- 25: KNN for Regression
- 26: Lazy Learning
- 29: Leaf Node
- 32: Information Gain
- 33: Gini Impurity
- 34: Pruning
- 37: Tree Depth
- 39: Continuous Features
- 40: Feature Space Partitioning
- 42: Sigmoid Function
- 43: Log-Loss
- 44: Binary Classification
- 46: Maximum Likelihood
- 47: One-vs-All
...and 92 more
Connected Components¶
- Number of Connected Components: 1
✅ All concepts are connected in a single graph.
Indegree Analysis¶
Top 10 concepts that are prerequisites for the most other concepts:
| Rank | Concept ID | Concept Label | Indegree |
|---|---|---|---|
| 1 | 82 | Neural Network | 15 |
| 2 | 6 | Training Data | 11 |
| 3 | 13 | Model | 10 |
| 4 | 14 | Algorithm | 10 |
| 5 | 116 | Convolutional Neural Network | 10 |
| 6 | 4 | Classification | 9 |
| 7 | 9 | Feature | 9 |
| 8 | 70 | K-Means Clustering | 9 |
| 9 | 2 | Supervised Learning | 8 |
| 10 | 55 | Support Vector Machine | 8 |
Outdegree Distribution¶
| Dependencies | Number of Concepts |
|---|---|
| 0 | 1 |
| 1 | 113 |
| 2 | 82 |
| 3 | 4 |
Recommendations¶
- ✅ DAG structure verified: Graph supports valid learning progressions
- ⚠️ Many orphaned nodes (112): Consider if these should be prerequisites for advanced concepts
- ℹ️ Consider adding cross-dependencies: More connections could create richer learning pathways
Report generated by learning-graph-reports/analyze_graph.py