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The fraud identification models were build using Python Scikit-learn machine-learning module.

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lasanthagithub/Identifying_Fraud_from_Enron_Emails_using_Machine_Learning

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__pycache__

__pycache__

 
 

.gitignore

.gitignore

 
 

Enron_emails_analysis_project_report_revision1.docx

Enron_emails_analysis_project_report_revision1.docx

 
 

Enron_emails_analysis_project_report_revision1.pdf

Enron_emails_analysis_project_report_revision1.pdf

 
 

README.md

README.md

 
 

enron61702insiderpay.pdf

enron61702insiderpay.pdf

 
 

final_project_dataset.pkl

final_project_dataset.pkl

 
 

final_project_dataset_modified.pkl

final_project_dataset_modified.pkl

 
 

my_classifier.pkl

my_classifier.pkl

 
 

my_dataset.pkl

my_dataset.pkl

 
 

my_feature_list.pkl

my_feature_list.pkl

 
 

poi_email_addresses.py

poi_email_addresses.py

 
 

poi_id.py

poi_id.py

 
 

poi_names.txt

poi_names.txt

 
 

tester.py

tester.py

 
 

tester.pyc

tester.pyc

 
 

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Please see the file Enron_emails_analysis_project_report.pdf for details of the project.

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The fraud identification models were build using Python Scikit-learn machine-learning module.

Topics

python machine-learning random-forest scikit-learn cross-validation feature-selection feature-extraction classification regression-models principal-component-analysis svc fraud-detection model-building knearest-neighbor-classifier enron-emails

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