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Table · dataset · 2025

roberto-armas/ml_data_test_detection_bank_transaction_frauds_unbalanced

Listed in Hugging Face Datasets

ML Data Test Detection Bank Transaction Frauds Unbalanced The project provides a quick and accessible dataset designed for learning and experimenting with machine learning algorithms, specifically in the context of detecting fraudulent bank transactions.

Description

It is intended for practicing and applying concepts such as Random Forest, Support Vector Machines (SVM), and Synthetic Minority Over-sampling Technique (SMOTE) to address unbalanced classification problems.

Note

Read the rest (1 more)

This dataset is… See the full description on the dataset page: huggingface.co/datasets/roberto-armas/ml_data_test_detection_bank_transaction_frauds_unbalanced.

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Stated by source
tabular · text
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsroberto-armas/ml_data_test_detection_bank_transaction_frauds_unbalanced10 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:tabularsource · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0