Dominance Analysis for Attribution in Data Analytics
The article explains that attribution analysis of metric declines requires a quantitative approach, introducing Dominance Analysis—a econometric technique that decomposes regression R² into variable-specific contributions by fitting all subset models, averaging marginal effects, ranking factors, and providing a Python implementation with the dominance‑analysis package illustrated on the Boston Housing dataset.
Attribution analysis is a challenging yet essential task for data analysts, especially when dealing with declines in key metrics.
The article outlines three main characteristics of attribution analysis: it focuses on declines, requires timely response, and is difficult to derive causal insights without controlled experiments.
For simple fluctuations, quick diagnostic methods such as version bug checks, event checks, and funnel analysis are suggested. For complex cases, a quantitative method to assess each factor's contribution is needed.
The core objective is to quantify the contribution share of each explanatory variable to the target change.
The proposed method is Dominance Analysis, a technique from econometrics that decomposes the R² of a linear regression into variable-specific contributions.
Key steps include: (1) fitting all possible subset regressions, (2) averaging the marginal R² contributions across all variable elimination orders, and (3) ranking variables by their average contribution.
Implementation in Python uses the dominance-analysis package. Example code:
from dominance_analysis import Dominance_Datasets
from dominance_analysis import Dominance
boston_dataset = Dominance_Datasets.get_boston()
dominance_regression = Dominance(data=boston_dataset, target='House_Price', objective=1)
incremental_rsquare = dominance_regression.incremental_rsquare()
dominance_regression.plot_incremental_rsquare()
stats = dominance_regression.dominance_stats()These steps cover data preparation (using the Boston Housing dataset), variable comparison, visualization of incremental R², and extraction of detailed statistics.
The article concludes with references to foundational papers on dominance analysis and Shapley value decomposition.
DeWu Technology
A platform for sharing and discussing tech knowledge, guiding you toward the cloud of technology.
How this landed with the community
Was this worth your time?
0 Comments
Thoughtful readers leave field notes, pushback, and hard-won operational detail here.