XOPSIS: an explainable AI method based on the order of preference by similarity to ideal solution

XOPSIS: an explainable AI method based on the order of preference by similarity to ideal solution

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023.

Bibliografiske detaljer
Hovedforfatter:	Rahman, Anika
Andre forfattere:	Alam, Md. Golam Rabiul
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Explainable AI XOPSIS LIME SHAP Maternal health Interpretability Transparency Artificial intelligence
Online adgang:	http://hdl.handle.net/10361/22640

Lignende værker

Demystifying machine learning models for IOT attack detection with explainable AI
af: Muna, Rabeya Khatun, et al.
Udgivet: (2021)

Personalization in federated recommendation system using SVD++ with explainability
af: Patwary, Kabbya Kantam, et al.
Udgivet: (2022)

Voice impersonation detection using LSTM based RNN and explainable AI
af: Barua, Kawshik, et al.
Udgivet: (2022)

Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
af: Hossain, Mainul, et al.
Udgivet: (2022)

Bank loan prediction using machine learning
af: Mahottam, Parthosarothi, et al.
Udgivet: (2023)

A hybrid deep learning model and explainable AI-based Bengali hate speech multi-label classification and interpretation
af: Shakil, Mahmudul Hasan
Udgivet: (2023)

Heart attack prediction using machine learning and XAI
af: Ahsan, Mumtahina
Udgivet: (2023)

Exploring Alzheimer's disease prediction with XAI in various neural network models
af: Rahman, Quazi Ashikur, et al.
Udgivet: (2022)

Mobile sensors based human activity recognition using machine learning with explainable ML
af: Rahman, Raihan, et al.
Udgivet: (2021)

Quantum lattice learning and explainable artificial intelligence for maternal and child healthcare
af: Marvin, Ggaliwango
Udgivet: (2022)

Demystifying black-box learning models of rumor detection from social media posts
af: Tafannum, Faiza, et al.
Udgivet: (2021)

Advanced artificial intelligence self balanced robot for home security
af: Shourove, MD. Niaz Sharif, et al.
Udgivet: (2018)

The role of Artificial Intelligence (AI) in the detection and diagnosis of chronic diseases – a review
af: Zaman, Mumtahina
Udgivet: (2022)

PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
af: Rahman, Tahsinur, et al.
Udgivet: (2023)

Good governance and human development
af: Yadav, S.N
Udgivet: (2009)

Explainable artificial intelligence and model calibration for water quality prediction
af: Hellen, Nakayiza
Udgivet: (2022)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
af: Rahman, Masroor, et al.
Udgivet: (2023)

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
af: Niaz, H.M, et al.
Udgivet: (2024)

Transparency, efficiency, competitiveness and compliance of PPA 2006 &PPR 2008: a case study on BCIC based on KPIs
af: Biswas, Samir
Udgivet: (2017)

Will AI technology reduce job opportunities in future?
af: Kabir, Tasnim, et al.
Udgivet: (2024)

Impact of artificial intelligence in closing the gender gap among women-led industries: a developing country perspective
af: Basir, S M
Udgivet: (2024)

Implementing A.I based solutions to understand & predict consumer sentiment
af: Bin Ahmed, Omar
Udgivet: (2023)

Investigation on the strategy and impact of artificial insemination programme and performance of Crossbred Cattle in Bangladesh
af: Majid, M.A., et al.
Udgivet: (2019)

Comparative analysis of machine learning models for stock price analysis across different dataset sizes
af: Srabon, Abir Alam, et al.
Udgivet: (2023)

Artificial intelligence: Essential to Successful Consumer Acquisition for the Consumer Electronics Goods Industry in Bangladesh. A study on Walton Hi Tech Industries Ltd.
af: Islam, MD. Wasib
Udgivet: (2023)

Demystify the blackbox model of automated detection of lung and kidney diseases from X-ray and CT radiographs
af: Islam, Md. Nazmul
Udgivet: (2023)

Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models
af: Barua, Debalina
Udgivet: (2023)

Making AI intelligible :
af: Cappelen, Herman

Mitigation of hallucination and interpretations of self attention of Mistral 7B AI to analyze and visualize context understanding ability of large language models
af: Taki, S.M. Abrar Mustakim, et al.
Udgivet: (2024)

Introduction to AI robotics /
af: Murphy, Robin, 1957-
Udgivet: (2000)

To Afghanistan concerning data transparency among government agencies
af: Quraishi, Haseebullah
Udgivet: (2019)

Yoga posture recognition using the deep learning process
af: Islam, Abidul, et al.
Udgivet: (2023)

Predicting obesity: a comparative analysis of machine learning models incorporating different features
af: Rahman, Md.Sakibur, et al.
Udgivet: (2023)

The impact of artificial intelligence on the financial sector
af: Siddiqui, Ria
Udgivet: (2024)

Slides /
af: Kueter, Roger A.
Udgivet: (1981)

Maternity leave: (A study of its impact on female employees in organisations in Dhaka Bangladesh)
af: Chowdhury, Shaan Ahmed
Udgivet: (2023)

Ideal solution of college linear algebra : theory of matrices /
af: Rahman, Md. Abdur
Udgivet: (1986)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
af: Farhan, Rafid, et al.
Udgivet: (2024)

Implementation of reinforcement learning architecture to augment an AI that can self-learn to play video games
af: Mahmud, Aqil, et al.
Udgivet: (2023)

Women’s preferences for maternal healthcare services in Bangladesh: Evidence from a discrete choice experiment.
af: Mahumud, Rashidul Alam, et al.
Udgivet: (2022)