Influence Analysis
Explore how to identify and quantify the influence of individual nodes on a target variable within Bayesian networks. Learn to run ablation experiments to measure changes in probability distributions and visualize influence scores, improving your understanding of causal factors impacting project outcomes.
We'll cover the following...
In this lesson, we conduct a thorough analysis to identify the drift factors that significantly influence the causal network. These factors are critical in steering the behavior and outcomes within our network and, hence, play a vital role in our analysis.
This initial analysis stage is crucial as it allows us to pinpoint the primary causes behind our specified project's problems. By identifying these influential drift factors, we can develop a deep understanding of the project's underlying issues and devise more targeted and effective solutions.
Influences on the final model
To evaluate the influence of one node over the target node "Overcost", we can perform ablation experiments. This involves removing the evidence for one ...