Search Results for author:
Found 4 papers, 3 papers with code
The Berkelmans-Pries Feature Importance Method: A Generic Measure of Informativeness of Features
We prove that our method has many useful properties, and accurately predicts the correct FI values for several cases where the ground truth FI can be derived in an exact manner.
The Optimal Input-Independent Baseline for Binary Classification: The Dutch Draw
The goal of this paper is to examine all baseline methods that are independent of feature values and determine which model is the `best' and why.
The Dutch Draw: Constructing a Universal Baseline for Binary Prediction Models
Summarizing, the DD baseline is: (1) general, as it is applicable to all binary classification problems; (2) simple, as it is quickly determined without training or parameter-tuning; (3) informative, as insightful conclusions can be drawn from the results.
The BP Dependency Function: a Generic Measure of Dependence between Random Variables
To this end, we also provide Python code to determine the dependency function for use in practice.
