The purpose of this project is to predict whether an individual is a person of interest. The dataset includes 18 POI and 128 non-POI, for a total number of 146 data points. For each individual, the dataset provides these 21 features:
a. financial features: ['salary', 'deferral_payments', 'total_payments', 'loan_advances', 'bonus', 'restricted_stock_deferred', 'deferred_income', 'total_stock_value', 'expenses', 'exercised_stock_options', 'other', 'long_term_incentive', 'restricted_stock', 'director_fees'] (all units are in US dollars) b. email features: ['to_messages', 'email_address', 'from_poi_to_this_person', 'from_messages', 'from_this_person_to_poi', 'shared_receipt_with_poi'] (units are generally number of emails messages; notable exception is ‘email_address’, which is a text string) c. POI label: [‘poi’] (boolean, represented as integer)
The report for the project is at enron_report.pdf.
This project is part of the Udacity Data Analyst Nanodegree.