bayesian-network-analyzer - Bayesian Network Analyzer for Probabilistic Reasoning
Construct and analyze Bayesian networks for probabilistic inference and causal analysis
Tags
Updated: 2026-03-09Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Learn DAG structure from data
- Estimate conditional probability tables
- Perform belief propagation and inference
- Estimate causal effects
- Analyze sensitivity to evidence
- Evaluate what-if scenarios
- Visualize network structures
- Integrate with external data sources
Inputs
- Network structure definition
- Conditional probability tables
- Query type and target variables
- Inference algorithm options
- Evidence for conditional queries
Outputs
- Query result probabilities
- Most likely state assignments
- Causal effect estimates
- Sensitivity analysis reports
- Network visualization files
Requirements
- Python environment
- pgmpy library
- pomegranate library
- bnlearn library
- pyAgrum library