Electricity Consumption Invoice Data

Cite this dataset

Wan Nur Atirah Wan Mohd Adnan (2021) Electricity Consumption Invoice Data. [Dataset]

Description

This is pre-processed data of fraud detection in electricity and gas consumption obtained from Kaggle, an open-source website for data. There are two datasets. The first dataset is the pre-processed data where the duplicates and missing values have already been removed. The data had also been filtered to consist of only rows of data for electricity consumption, client category of 11, the counter coefficient is one and lastly, invoices dated in 2019 are included for model training.

Metadata


Item Type: Dataset
Creators: Wan Nur Atirah Wan Mohd Adnan
Additional Information: Steps to reproduce. 1) The client and invoice data are merged using the one-to-many option. 2) Duplicates and missing values removed. 3) Select counter_type = 'ELEC', client_catg = 11, counter_coefficient = 1 and invoice_date of 2019 only. 4) The numbering of the categorical variable is reassigned with a new numbering except for counter_statue and target. 5) Standardization applied to the continuous variables. 6) Apply random undersampling with a factor of 0.06 for non-fraud and 1 for fraud. (2nd dataset only)
Keywords: Machine Learning, Detection Technique, Fraud
Subjects: Science and Technology > Computing, Informatics and Mathematics
Research Fields: Computer Science, Information Technology and Telecommunications
Divisions: Computing, Informatics and Mathematics
Date: 30 September 2021
Date Deposited: 02 Aug 2023 03:58
Identification Number (DOI): 10.17632/nwwvh8nt63.2
Related URLs:
URI: http://data.uitm.edu.my/id/eprint/6

Files


[thumbnail of Version 2] Spreadsheet (Version 2) [Data Collection]
merged_train_cleaned.csv - Published Version
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[thumbnail of Version 2] Spreadsheet (Version 2) [Data Collection]
merged_train_cleaned.sav - Published Version
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[thumbnail of Version 2] Spreadsheet (Version 2) [Data Collection]
RUS_1.csv - Published Version
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[thumbnail of Version 2] Spreadsheet (Version 2) [Data Collection]
RUS_1.sav - Published Version
Available under License Creative Commons Attribution.

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