Financial

Alternative names: loan application

PKDD'99 Financial dataset contains 606 successful and 76 not successful loans along with their information and transactions.

Original source: lisp.vse.cz (BibTeX)

Financial (by Jan Motl)
- add foreign key constrains, separate "rodne cislo" into date of birth and gender
Financial_ijs (by Janez Kranjc)
Financial_std (by Oliver Schulte)

Dataset details

Associated task:

Classification

Domain:

Financial

Data types:

Size:

78.8 MB

Count of tables:

Count of rows:

1,090,086

Count of columns:

Missing values:

Yes

Compound keys:

Loops:

Yes

Dataset version	Target	Algorithm	Author text	Measure	Value
financial	status	Aleph	Constrained Sequential Pattern Knowledge in Multi-Relational Learning	Accuracy	0.71
financial	status	Aleph	Wordification: Propositionalization by unfolding relational data into bags of words	Accuracy	0.8675
financial	status	CoTReC	Transductive Relational Classification in the Co-training Paradigm	Accuracy	0.8811
financial	status	CrossMine	A Heterogeneous Naive-Bayesian Classifier for Relational Databases	Accuracy	0.85
financial	status	CrossMine	ADMA 2010	Accuracy	0.873
financial	status	CrossMine	Efficient Classification across Multiple Database Relations: A CrossMine Approach	Accuracy	0.895
financial	status	CrossMine	Learning from Skewed Class Multi-relational Databases	Accuracy	0.793
financial	status	CrossMine	Relational Classification using Multiple View Approach with Voting	Accuracy	0.903
financial	status	E-NB	A Hierarchy of Independence Assumptions for Multi-relational Bayes Net Classifiers	F-measure	0.84
financial	status	E-NB	A Hierarchy of Independence Assumptions for Multi-relational Bayes Net Classifiers	AUC ROC	0.85
Show all algorithms

The datasets are publicly available directly from MariaDB database.

Open your favourite MariaDB client (MySQL Workbench works, but see FAQ)
Use following credentials:
- hostname: relational.fit.cvut.cz
- port: 3306
- username: guest
- password: relational
Export "financial" database (or other version of the dataset, if available) in your favourite format (e.g. CSV or SQL dump).