SlideShare une entreprise Scribd logo
1  sur  30
Minority Report in Fraud Detection: Classification of Skewed Data Clifton Phua, Damminda Alahakoon, and Vincent Lee SIGKDD 2004 Reporter: Ping-Hua Yang
Abstract ,[object Object],[object Object],[object Object],[object Object]
Outline  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Introduction  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fraud detection ,[object Object],[object Object],[object Object]
Existing Fraud detection methods ,[object Object],[object Object],[object Object],[object Object],[object Object]
Existing Fraud detection methods ,[object Object],[object Object]
The New Fraud detection method ,[object Object]
Fraud detection algorithms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experiments ,[object Object],[object Object],[object Object],[object Object]
Data Understanding ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cost Model ,[object Object],[object Object],[object Object],[object Object]
Cost Model ,[object Object]
Data preparation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data preparation ,[object Object],[object Object],[object Object],[object Object]
M odeling
Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Modeling
Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Results ,[object Object],[object Object]
Results ,[object Object],[object Object]
Results
Results  ,[object Object],[object Object],[object Object],[object Object]
Discussion ,[object Object],[object Object],[object Object]
Discussion
Discussion ,[object Object]
Conclusion  ,[object Object],[object Object],[object Object]

Contenu connexe

Tendances

Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...ahmad abdelhafeez
 
MATH 533 Education Specialist / snaptutorial.com
MATH 533 Education Specialist / snaptutorial.comMATH 533 Education Specialist / snaptutorial.com
MATH 533 Education Specialist / snaptutorial.comMcdonaldRyan97
 
Probability density estimation using Product of Conditional Experts
Probability density estimation using Product of Conditional ExpertsProbability density estimation using Product of Conditional Experts
Probability density estimation using Product of Conditional ExpertsChirag Gupta
 
Multi-Cluster Based Approach for skewed Data in Data Mining
Multi-Cluster Based Approach for skewed Data in Data MiningMulti-Cluster Based Approach for skewed Data in Data Mining
Multi-Cluster Based Approach for skewed Data in Data MiningIOSR Journals
 
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...Seval Çapraz
 
Econometrics of High-Dimensional Sparse Models
Econometrics of High-Dimensional Sparse ModelsEconometrics of High-Dimensional Sparse Models
Econometrics of High-Dimensional Sparse ModelsNBER
 
Spectral Element Methods in Large Eddy Simulation
Spectral Element Methods in Large Eddy SimulationSpectral Element Methods in Large Eddy Simulation
Spectral Element Methods in Large Eddy Simulationgaurav dhir
 
Prediction model of algal blooms using logistic regression and confusion matrix
Prediction model of algal blooms using logistic regression and confusion matrix Prediction model of algal blooms using logistic regression and confusion matrix
Prediction model of algal blooms using logistic regression and confusion matrix IJECEIAES
 
Multiclass classification of imbalanced data
Multiclass classification of imbalanced dataMulticlass classification of imbalanced data
Multiclass classification of imbalanced dataSaurabhWani6
 
Use of Definitive Screening Designs to Optimize an Analytical Method
Use of Definitive Screening Designs to Optimize an Analytical MethodUse of Definitive Screening Designs to Optimize an Analytical Method
Use of Definitive Screening Designs to Optimize an Analytical MethodPhilip Ramsey
 
Modeling strategies for definitive screening designs using jmp and r
Modeling strategies for definitive  screening designs using jmp and rModeling strategies for definitive  screening designs using jmp and r
Modeling strategies for definitive screening designs using jmp and rPhilip Ramsey
 
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...A Mathematical Programming Approach for Selection of Variables in Cluster Ana...
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...IJRES Journal
 
Simulation Study of Hurdle Model Performance on Zero Inflated Count Data
Simulation Study of Hurdle Model Performance on Zero Inflated Count DataSimulation Study of Hurdle Model Performance on Zero Inflated Count Data
Simulation Study of Hurdle Model Performance on Zero Inflated Count DataIan Camacho
 
A Combined Approach for Feature Subset Selection and Size Reduction for High ...
A Combined Approach for Feature Subset Selection and Size Reduction for High ...A Combined Approach for Feature Subset Selection and Size Reduction for High ...
A Combined Approach for Feature Subset Selection and Size Reduction for High ...IJERA Editor
 
Non-parametric analysis of models and data
Non-parametric analysis of models and dataNon-parametric analysis of models and data
Non-parametric analysis of models and datahaharrington
 
MATH 533 RANK Achievement Education--math533rank.com
MATH 533 RANK Achievement Education--math533rank.comMATH 533 RANK Achievement Education--math533rank.com
MATH 533 RANK Achievement Education--math533rank.comkopiko162
 

Tendances (19)

Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
 
MATH 533 Education Specialist / snaptutorial.com
MATH 533 Education Specialist / snaptutorial.comMATH 533 Education Specialist / snaptutorial.com
MATH 533 Education Specialist / snaptutorial.com
 
Probability density estimation using Product of Conditional Experts
Probability density estimation using Product of Conditional ExpertsProbability density estimation using Product of Conditional Experts
Probability density estimation using Product of Conditional Experts
 
Statsci
StatsciStatsci
Statsci
 
Multi-Cluster Based Approach for skewed Data in Data Mining
Multi-Cluster Based Approach for skewed Data in Data MiningMulti-Cluster Based Approach for skewed Data in Data Mining
Multi-Cluster Based Approach for skewed Data in Data Mining
 
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...
Statistical Data Analysis on a Data Set (Diabetes 130-US hospitals for years ...
 
FSRM 582 Project
FSRM 582 ProjectFSRM 582 Project
FSRM 582 Project
 
Econometrics of High-Dimensional Sparse Models
Econometrics of High-Dimensional Sparse ModelsEconometrics of High-Dimensional Sparse Models
Econometrics of High-Dimensional Sparse Models
 
Spectral Element Methods in Large Eddy Simulation
Spectral Element Methods in Large Eddy SimulationSpectral Element Methods in Large Eddy Simulation
Spectral Element Methods in Large Eddy Simulation
 
Prediction model of algal blooms using logistic regression and confusion matrix
Prediction model of algal blooms using logistic regression and confusion matrix Prediction model of algal blooms using logistic regression and confusion matrix
Prediction model of algal blooms using logistic regression and confusion matrix
 
Multiclass classification of imbalanced data
Multiclass classification of imbalanced dataMulticlass classification of imbalanced data
Multiclass classification of imbalanced data
 
Use of Definitive Screening Designs to Optimize an Analytical Method
Use of Definitive Screening Designs to Optimize an Analytical MethodUse of Definitive Screening Designs to Optimize an Analytical Method
Use of Definitive Screening Designs to Optimize an Analytical Method
 
Modeling strategies for definitive screening designs using jmp and r
Modeling strategies for definitive  screening designs using jmp and rModeling strategies for definitive  screening designs using jmp and r
Modeling strategies for definitive screening designs using jmp and r
 
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...A Mathematical Programming Approach for Selection of Variables in Cluster Ana...
A Mathematical Programming Approach for Selection of Variables in Cluster Ana...
 
Simulation Study of Hurdle Model Performance on Zero Inflated Count Data
Simulation Study of Hurdle Model Performance on Zero Inflated Count DataSimulation Study of Hurdle Model Performance on Zero Inflated Count Data
Simulation Study of Hurdle Model Performance on Zero Inflated Count Data
 
A Combined Approach for Feature Subset Selection and Size Reduction for High ...
A Combined Approach for Feature Subset Selection and Size Reduction for High ...A Combined Approach for Feature Subset Selection and Size Reduction for High ...
A Combined Approach for Feature Subset Selection and Size Reduction for High ...
 
Non-parametric analysis of models and data
Non-parametric analysis of models and dataNon-parametric analysis of models and data
Non-parametric analysis of models and data
 
JEDM_RR_JF_Final
JEDM_RR_JF_FinalJEDM_RR_JF_Final
JEDM_RR_JF_Final
 
MATH 533 RANK Achievement Education--math533rank.com
MATH 533 RANK Achievement Education--math533rank.comMATH 533 RANK Achievement Education--math533rank.com
MATH 533 RANK Achievement Education--math533rank.com
 

En vedette

Bridgestreet Worldwide Corporate/Temporary Housing
Bridgestreet Worldwide Corporate/Temporary HousingBridgestreet Worldwide Corporate/Temporary Housing
Bridgestreet Worldwide Corporate/Temporary Housingualaning
 
Profesionales 2.0. Los nuevos empleos TIC
Profesionales 2.0. Los nuevos empleos TICProfesionales 2.0. Los nuevos empleos TIC
Profesionales 2.0. Los nuevos empleos TICarcademayhem
 
Luna de avellaneda
Luna de avellanedaLuna de avellaneda
Luna de avellanedafernagiron
 
Detecting fraud in cellular telephone networks
Detecting fraud in cellular telephone networksDetecting fraud in cellular telephone networks
Detecting fraud in cellular telephone networksJamal Meselmani
 
Fraud Detector - The easy-to-customize, high ROI, IT solution for detecting ...
Fraud Detector - The easy-to-customize, high ROI,  IT solution for detecting ...Fraud Detector - The easy-to-customize, high ROI,  IT solution for detecting ...
Fraud Detector - The easy-to-customize, high ROI, IT solution for detecting ...112Motion
 
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...Reynolds Center for Business Journalism
 
Graphes et détection de fraude : exemple de l'assurance
Graphes et détection de fraude : exemple de l'assuranceGraphes et détection de fraude : exemple de l'assurance
Graphes et détection de fraude : exemple de l'assuranceLinkurious
 
Insurance fraud through collusion - Pierre Picard
Insurance fraud through collusion - Pierre PicardInsurance fraud through collusion - Pierre Picard
Insurance fraud through collusion - Pierre PicardKezhan SHI
 
Détection de profils, application en santé et en économétrie geissler
Détection de profils, application en santé et en économétrie   geisslerDétection de profils, application en santé et en économétrie   geissler
Détection de profils, application en santé et en économétrie geisslerKezhan SHI
 
Scalable Prediction Services with R
Scalable Prediction Services with RScalable Prediction Services with R
Scalable Prediction Services with RJustin Kamerman
 
Building Scalable Prediction Services in R
Building Scalable Prediction Services in RBuilding Scalable Prediction Services in R
Building Scalable Prediction Services in RWork-Bench
 
Detecting fraud with Python and machine learning
Detecting fraud with Python and machine learningDetecting fraud with Python and machine learning
Detecting fraud with Python and machine learningwgyn
 
Machine Learning for Fraud Detection
Machine Learning for Fraud DetectionMachine Learning for Fraud Detection
Machine Learning for Fraud DetectionNitesh Kumar
 
Telecom Fraud Detection - Naive Bayes Classification
Telecom Fraud Detection - Naive Bayes ClassificationTelecom Fraud Detection - Naive Bayes Classification
Telecom Fraud Detection - Naive Bayes ClassificationMaruthi Nataraj K
 
Detecting Fraud Using Data Mining Techniques
Detecting Fraud Using Data Mining TechniquesDetecting Fraud Using Data Mining Techniques
Detecting Fraud Using Data Mining TechniquesDecosimoCPAs
 

En vedette (20)

Bridgestreet Worldwide Corporate/Temporary Housing
Bridgestreet Worldwide Corporate/Temporary HousingBridgestreet Worldwide Corporate/Temporary Housing
Bridgestreet Worldwide Corporate/Temporary Housing
 
2008peno1milieu
2008peno1milieu2008peno1milieu
2008peno1milieu
 
Profesionales 2.0. Los nuevos empleos TIC
Profesionales 2.0. Los nuevos empleos TICProfesionales 2.0. Los nuevos empleos TIC
Profesionales 2.0. Los nuevos empleos TIC
 
Luna de avellaneda
Luna de avellanedaLuna de avellaneda
Luna de avellaneda
 
Detecting fraud in cellular telephone networks
Detecting fraud in cellular telephone networksDetecting fraud in cellular telephone networks
Detecting fraud in cellular telephone networks
 
Fraud Detector - The easy-to-customize, high ROI, IT solution for detecting ...
Fraud Detector - The easy-to-customize, high ROI,  IT solution for detecting ...Fraud Detector - The easy-to-customize, high ROI,  IT solution for detecting ...
Fraud Detector - The easy-to-customize, high ROI, IT solution for detecting ...
 
Detecting Frauds
Detecting FraudsDetecting Frauds
Detecting Frauds
 
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...
Detecting Corporate Fraud: Tips from a Crook and a Sleuth by Roddy Boyd and S...
 
Graphes et détection de fraude : exemple de l'assurance
Graphes et détection de fraude : exemple de l'assuranceGraphes et détection de fraude : exemple de l'assurance
Graphes et détection de fraude : exemple de l'assurance
 
Insurance fraud through collusion - Pierre Picard
Insurance fraud through collusion - Pierre PicardInsurance fraud through collusion - Pierre Picard
Insurance fraud through collusion - Pierre Picard
 
Détection de profils, application en santé et en économétrie geissler
Détection de profils, application en santé et en économétrie   geisslerDétection de profils, application en santé et en économétrie   geissler
Détection de profils, application en santé et en économétrie geissler
 
Scalable Prediction Services with R
Scalable Prediction Services with RScalable Prediction Services with R
Scalable Prediction Services with R
 
Urso construction fraud
Urso construction  fraudUrso construction  fraud
Urso construction fraud
 
Building Scalable Prediction Services in R
Building Scalable Prediction Services in RBuilding Scalable Prediction Services in R
Building Scalable Prediction Services in R
 
R at Microsoft
R at MicrosoftR at Microsoft
R at Microsoft
 
Detecting fraud with Python and machine learning
Detecting fraud with Python and machine learningDetecting fraud with Python and machine learning
Detecting fraud with Python and machine learning
 
Machine Learning for Fraud Detection
Machine Learning for Fraud DetectionMachine Learning for Fraud Detection
Machine Learning for Fraud Detection
 
Fraud Detection Architecture
Fraud Detection ArchitectureFraud Detection Architecture
Fraud Detection Architecture
 
Telecom Fraud Detection - Naive Bayes Classification
Telecom Fraud Detection - Naive Bayes ClassificationTelecom Fraud Detection - Naive Bayes Classification
Telecom Fraud Detection - Naive Bayes Classification
 
Detecting Fraud Using Data Mining Techniques
Detecting Fraud Using Data Mining TechniquesDetecting Fraud Using Data Mining Techniques
Detecting Fraud Using Data Mining Techniques
 

Similaire à 11/04 Regular Meeting: Monority Report in Fraud Detection Classification of Skewed Data

Automobile Insurance Claim Fraud Detection using Random Forest and ADASYN
Automobile Insurance Claim Fraud Detection using Random Forest and ADASYNAutomobile Insurance Claim Fraud Detection using Random Forest and ADASYN
Automobile Insurance Claim Fraud Detection using Random Forest and ADASYNIRJET Journal
 
Analysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through ApplicationAnalysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through Applicationaciijournal
 
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATION
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATIONANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATION
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATIONaciijournal
 
Predicting automobile insurance fraud using classical and machine learning mo...
Predicting automobile insurance fraud using classical and machine learning mo...Predicting automobile insurance fraud using classical and machine learning mo...
Predicting automobile insurance fraud using classical and machine learning mo...IJECEIAES
 
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...ahmad abdelhafeez
 
Analysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through ApplicationAnalysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through Applicationaciijournal
 
Accounting for variance in machine learning benchmarks
Accounting for variance in machine learning benchmarksAccounting for variance in machine learning benchmarks
Accounting for variance in machine learning benchmarksDevansh16
 
Building_a_Readmission_Model_Using_WEKA
Building_a_Readmission_Model_Using_WEKABuilding_a_Readmission_Model_Using_WEKA
Building_a_Readmission_Model_Using_WEKASunil Kakade
 
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTION
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTIONA MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTION
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTIONIJCI JOURNAL
 
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...Daniel Katz
 
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETS
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETSA HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETS
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETSEditor IJCATR
 
Machine learning for sanctions screening
Machine learning for sanctions screeningMachine learning for sanctions screening
Machine learning for sanctions screeningEnigma
 
Automobile Insurance Claim Fraud Detection
Automobile Insurance Claim Fraud DetectionAutomobile Insurance Claim Fraud Detection
Automobile Insurance Claim Fraud DetectionIRJET Journal
 
Empirical analysis of ensemble methods for the classification of robocalls in...
Empirical analysis of ensemble methods for the classification of robocalls in...Empirical analysis of ensemble methods for the classification of robocalls in...
Empirical analysis of ensemble methods for the classification of robocalls in...IJECEIAES
 
Classification of Breast Cancer Diseases using Data Mining Techniques
Classification of Breast Cancer Diseases using Data Mining TechniquesClassification of Breast Cancer Diseases using Data Mining Techniques
Classification of Breast Cancer Diseases using Data Mining Techniquesinventionjournals
 
Cyb 5675 class project final
Cyb 5675   class project finalCyb 5675   class project final
Cyb 5675 class project finalCraig Cannon
 
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdf
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdfTanvi_Sharma_Shruti_Garg_pre.pdf.pdf
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdfShrutiGarg649495
 
Re-mining item associations: Methodology and a case study in apparel retailing
Re-mining item associations: Methodology and a case study in apparel retailingRe-mining item associations: Methodology and a case study in apparel retailing
Re-mining item associations: Methodology and a case study in apparel retailingGurdal Ertek
 
Paper-Allstate-Claim-Severity
Paper-Allstate-Claim-SeverityPaper-Allstate-Claim-Severity
Paper-Allstate-Claim-SeverityGon-soo Moon
 

Similaire à 11/04 Regular Meeting: Monority Report in Fraud Detection Classification of Skewed Data (20)

Automobile Insurance Claim Fraud Detection using Random Forest and ADASYN
Automobile Insurance Claim Fraud Detection using Random Forest and ADASYNAutomobile Insurance Claim Fraud Detection using Random Forest and ADASYN
Automobile Insurance Claim Fraud Detection using Random Forest and ADASYN
 
Analysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through ApplicationAnalysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through Application
 
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATION
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATIONANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATION
ANALYSIS OF COMMON SUPERVISED LEARNING ALGORITHMS THROUGH APPLICATION
 
Predicting automobile insurance fraud using classical and machine learning mo...
Predicting automobile insurance fraud using classical and machine learning mo...Predicting automobile insurance fraud using classical and machine learning mo...
Predicting automobile insurance fraud using classical and machine learning mo...
 
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classif...
 
Analysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through ApplicationAnalysis of Common Supervised Learning Algorithms Through Application
Analysis of Common Supervised Learning Algorithms Through Application
 
Accounting for variance in machine learning benchmarks
Accounting for variance in machine learning benchmarksAccounting for variance in machine learning benchmarks
Accounting for variance in machine learning benchmarks
 
Building_a_Readmission_Model_Using_WEKA
Building_a_Readmission_Model_Using_WEKABuilding_a_Readmission_Model_Using_WEKA
Building_a_Readmission_Model_Using_WEKA
 
C0413016018
C0413016018C0413016018
C0413016018
 
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTION
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTIONA MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTION
A MODEL-BASED APPROACH MACHINE LEARNING TO SCALABLE PORTFOLIO SELECTION
 
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...
Legal Analytics Course - Class 6 - Overfitting, Underfitting, & Cross-Validat...
 
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETS
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETSA HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETS
A HYBRID MODEL FOR MINING MULTI DIMENSIONAL DATA SETS
 
Machine learning for sanctions screening
Machine learning for sanctions screeningMachine learning for sanctions screening
Machine learning for sanctions screening
 
Automobile Insurance Claim Fraud Detection
Automobile Insurance Claim Fraud DetectionAutomobile Insurance Claim Fraud Detection
Automobile Insurance Claim Fraud Detection
 
Empirical analysis of ensemble methods for the classification of robocalls in...
Empirical analysis of ensemble methods for the classification of robocalls in...Empirical analysis of ensemble methods for the classification of robocalls in...
Empirical analysis of ensemble methods for the classification of robocalls in...
 
Classification of Breast Cancer Diseases using Data Mining Techniques
Classification of Breast Cancer Diseases using Data Mining TechniquesClassification of Breast Cancer Diseases using Data Mining Techniques
Classification of Breast Cancer Diseases using Data Mining Techniques
 
Cyb 5675 class project final
Cyb 5675   class project finalCyb 5675   class project final
Cyb 5675 class project final
 
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdf
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdfTanvi_Sharma_Shruti_Garg_pre.pdf.pdf
Tanvi_Sharma_Shruti_Garg_pre.pdf.pdf
 
Re-mining item associations: Methodology and a case study in apparel retailing
Re-mining item associations: Methodology and a case study in apparel retailingRe-mining item associations: Methodology and a case study in apparel retailing
Re-mining item associations: Methodology and a case study in apparel retailing
 
Paper-Allstate-Claim-Severity
Paper-Allstate-Claim-SeverityPaper-Allstate-Claim-Severity
Paper-Allstate-Claim-Severity
 

Dernier

Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherRemote DBA Services
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfhans926745
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
Evaluating the top large language models.pdf
Evaluating the top large language models.pdfEvaluating the top large language models.pdf
Evaluating the top large language models.pdfChristopherTHyatt
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 

Dernier (20)

Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Evaluating the top large language models.pdf
Evaluating the top large language models.pdfEvaluating the top large language models.pdf
Evaluating the top large language models.pdf
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 

11/04 Regular Meeting: Monority Report in Fraud Detection Classification of Skewed Data

  • 1. Minority Report in Fraud Detection: Classification of Skewed Data Clifton Phua, Damminda Alahakoon, and Vincent Lee SIGKDD 2004 Reporter: Ping-Hua Yang
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 18.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 26.
  • 27.
  • 29.
  • 30.