arXiv:1804.08675
Data-Driven Investigative Journalism For Connectas Dataset
원문 초록
The following paper explores the possibility of using Machine Learning algorithms to detect the cases of corruption and malpractice by governments. The dataset used by the authors contains information about several government contracts in Colombia from year 2007 to 2012. The authors begin with exploring and cleaning the data, followed by which they perform feature engineering before finally implementing Machine Learning models to detect anomalies in the given dataset.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Repurposing recidivism models for forecasting police officer use of force
Extraction of Heart Rate from PPG Signal: A Machine Learning Approach using Decision Tree Regression Algorithm
ATM: A distributed, collaborative, scalable system for automated machine learning
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes
Comparing the Effects of Persistence Barcodes Aggregation and Feature Concatenation on Medical Imaging
토론
이 논문과 연결된 포럼 글이 아직 없습니다.