Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

5 November 2015

Papers citing "Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model"

50 / 110 papers shown

Title
Genos: General In-Network Unsupervised Intrusion Detection by Rule Extraction Ruoyu Li Qing Li Yu Zhang Dan Zhao Xi Xiao Yong-jia Jiang 45 3 0 28 Mar 2024
Information Cascade Prediction under Public Emergencies: A Survey Qi Zhang Guang Wang Li Lin Kaiwen Xia Shuai Wang AI4CE 28 1 0 28 Mar 2024
Dissecting users' needs for search result explanations Prerna Juneja Wenjuan Zhang Alison Smith-Renner Hemank Lamba Joel R. Tetreault Alex Jaimes FAtt 31 5 0 29 Jan 2024
Interpretable Reinforcement Learning for Robotics and Continuous Control Rohan R. Paleja Letian Chen Yaru Niu Andrew Silva Zhaoxin Li ... K. Chang H. E. Tseng Yan Wang S. Nageshrao Matthew C. Gombolay 44 7 0 16 Nov 2023
Learning Interpretable Rules for Scalable Data Representation and Classification Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 35 7 0 22 Oct 2023
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction Yang Wu Xurui Li Xuhong Zhang Yangyang Kang Changlong Sun Xiaozhong Liu 32 3 0 06 Sep 2023
Feature Importance Measurement based on Decision Tree Sampling Chao Huang Diptesh Das Koji Tsuda FAtt 31 2 0 25 Jul 2023
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation Ruitao Xie Jingbang Chen Limai Jiang Ru Xiao Yi-Lun Pan Yunpeng Cai GAN MedIm 27 0 0 12 Jun 2023
Interpretable Differencing of Machine Learning Models Swagatam Haldar Diptikalyan Saha Dennis L. Wei Rahul Nair Elizabeth M. Daly 16 1 0 10 Jun 2023
Explainable Machine Learning for Categorical and Mixed Data with Lossless Visualization Boris Kovalerchuk Elijah McCoy 17 3 0 29 May 2023
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models Julien N. Siems Konstantin Ditschuneit Winfried Ripken Alma Lindborg Maximilian Schambach Johannes Otterbach Martin Genzel 34 6 0 19 May 2023
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When? M. Rubaiyat Hossain Mondal Prajoy Podder 28 56 0 10 Apr 2023
From Conception to Deployment: Intelligent Stroke Prediction Framework using Machine Learning and Performance Evaluation Leila Ismail Huned Materwala 8 5 0 01 Apr 2023
Goal Driven Discovery of Distributional Differences via Language Descriptions Ruiqi Zhong Peter Zhang Steve Li Jinwoo Ahn Dan Klein Jacob Steinhardt 49 49 0 28 Feb 2023
A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas Janik-Vasily Benzin Stefanie Rinderle-Ma AI4TS 51 2 0 08 Feb 2023
Rationalizing Predictions by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 30 4 0 15 Jan 2023
Towards Reconciling Usability and Usefulness of Explainable AI Methodologies Pradyumna Tambwekar Matthew C. Gombolay 41 8 0 13 Jan 2023
Explainable AI for Bioinformatics: Methods, Tools, and Applications Md. Rezaul Karim Tanhim Islam Oya Beyan Christoph Lange Michael Cochez Dietrich-Rebholz Schuhmann Stefan Decker 34 68 0 25 Dec 2022
Why we do need Explainable AI for Healthcare Giovanni Cina Tabea E. Rober Rob Goedhart Ilker Birbil 37 14 0 30 Jun 2022
A Human-Centric Take on Model Monitoring Murtuza N. Shergadwala Himabindu Lakkaraju K. Kenthapadi 45 9 0 06 Jun 2022
bsnsing: A decision tree induction method based on recursive optimal boolean rule composition Yan-ching Liu 33 6 0 30 May 2022
Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel Ryuichi Kanoh M. Sugiyama 36 2 0 25 May 2022
Modern Views of Machine Learning for Precision Psychiatry Z. Chen Prathamesh Kulkarni Kulkarni I. Galatzer-Levy Benedetta Bigio C. Nasca Yu Zhang 57 91 0 04 Apr 2022
Making use of supercomputers in financial machine learning Philippe Cotte P. Lagier Vincent Margot Christoph F. Geißler 27 2 0 01 Mar 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving Rohan R. Paleja Yaru Niu Andrew Silva Chace Ritchie Sugju Choi Matthew C. Gombolay 32 16 0 04 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 194 186 0 03 Feb 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods Abhineet Agarwal Yan Shuo Tan Omer Ronen Chandan Singh Bin-Xia Yu 65 27 0 02 Feb 2022
Describing Differences between Text Distributions with Natural Language Ruiqi Zhong Charles Burton Snell Dan Klein Jacob Steinhardt VLM 134 42 0 28 Jan 2022
Towards Relatable Explainable AI with the Perceptual Process Wencan Zhang Brian Y. Lim AAML XAI 29 62 0 28 Dec 2021
Multiclass Optimal Classification Trees with SVM-splits V. Blanco Alberto Japón J. Puerto 16 6 0 16 Nov 2021
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds Yan Shuo Tan Abhineet Agarwal Bin Yu 27 10 0 18 Oct 2021
Scalable Rule-Based Representation Learning for Interpretable Classification Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 37 61 0 30 Sep 2021
An Exploration And Validation of Visual Factors in Understanding Classification Rule Sets Jun Yuan O. Nov E. Bertini 28 10 0 19 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 69 519 0 31 Aug 2021
Improving Human Sequential Decision-Making with Reinforcement Learning Hamsa Bastani Osbert Bastani W. Sinchaisri HAI OffRL 25 12 0 19 Aug 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lio Marco Maggini S. Melacci 42 69 0 11 Aug 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lio Marco Gori S. Melacci FAtt XAI 30 78 0 12 Jun 2021
Explainable Activity Recognition for Smart Home Systems Devleena Das Yasutaka Nishimura R. Vivek Naoto Takeda Sean T. Fish Thomas Ploetz Sonia Chernova 24 41 0 20 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 29 0 0 14 May 2021
On Guaranteed Optimal Robust Explanations for NLP Models Emanuele La Malfa A. Zbrzezny Rhiannon Michelmore Nicola Paoletti Marta Z. Kwiatkowska FAtt 19 47 0 08 May 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE) M. Virgolin A. D. Lorenzo Francesca Randone Eric Medvet M. Wahde 24 30 0 13 Apr 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice David S. Watson Limor Gultchin Ankur Taly Luciano Floridi 22 63 0 27 Mar 2021
Robust subgroup discovery Hugo Manuel Proença Peter Grünwald Thomas Bäck M. Leeuwen 23 11 0 25 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 655 0 20 Mar 2021
3D4ALL: Toward an Inclusive Pipeline to Classify 3D Contents Nahyun Kwon Chen Liang Jeeeun Kim DiffM 11 1 0 24 Feb 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 28 396 0 19 Oct 2020
A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing Ping Lang Xiongjun Fu M. Martorella Jian Dong Rui Qin Xianpeng Meng M. Xie 26 39 0 29 Sep 2020
Explainable Predictive Process Monitoring Musabir Musabayli F. Maggi Williams Rizzi Josep Carmona Chiara Di Francescomarino 19 60 0 04 Aug 2020