InfoGram and admissible machine learning
نویسندگان
چکیده
We have entered a new era of machine learning (ML), where the most accurate algorithm with superior predictive power may not even be deployable, unless it is admissible under regulatory constraints. This has led to great interest in developing fair, transparent and trustworthy ML methods. The purpose this article introduce information-theoretic framework (admissible learning) algorithmic risk-management tools (InfoGram, L-features, ALFA-testing) that can guide an analyst redesign off-the-shelf methods compliant, while maintaining good prediction accuracy. illustrated our approach using several real-data examples from financial sectors, biomedical research, marketing campaigns, criminal justice system.
منابع مشابه
Admissible Hypotheses and Enhanced Learning
This paper discusses s t ra teg ies fo r moving through sequences of hypotheses, each one of which is produced in response to an experimental tes t of the previous member. Previous discussions of t h i s issue have a l l agreed that hypotheses deduct ive ly incompat ible w i t h the evidence at stage ri cannot appear in the sequence beyond n This paper contends that t h i s conclusion is untena...
متن کاملLearning Admissible Heuristics while Solving Problems
A method is presented that causes A* to return high quality solutions whi le solving a set of problems using a non-admissible heuristic. The heuristic gu id ing the search changes as new informat ion is learned dur ing the search, and it converges to an admissible heuristic wh ich 'contains the insight ' of the or ig ina l nonadmissible one. After a finite number of problems, A * returns only o...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملDust source mapping using satellite imagery and machine learning models
Predicting dust sources area and determining the affecting factors is necessary in order to prioritize management and practice deal with desertification due to wind erosion in arid areas. Therefore, this study aimed to evaluate the application of three machine learning models (including generalized linear model, artificial neural network, random forest) to predict the vulnerability of dust cent...
متن کاملMachine learning algorithms in air quality modeling
Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Machine Learning
سال: 2022
ISSN: ['0885-6125', '1573-0565']
DOI: https://doi.org/10.1007/s10994-021-06121-4