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Statlog (German Credit Data)

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This dataset classifies people described by a set of attributes as good or bad credit risks. Comes in two formats (one all numeric). Also comes with a cost matrix Two datasets are provided. the original dataset, in the form provided by Prof. Hofmann, contains categorical/symbolic attributes and is in the file "german.data". For algorithms that need numerical attributes, Strathclyde University produced the file "german.data-numeric". This file has been edited and several indicator variables added to make it suitable for algorithms which cannot cope with categorical variables. Several attributes that are ordered categorical (such as attribute 17) have been coded as integer. This was the form used by StatLog. This dataset requires use of a cost matrix (see below) ..... 1 2 ---------------------------- 1 0 1 ----------------------- 2 5 0 (1 = Good, 2 = Bad) The rows represent the actual classification and the columns the predicted classification. It is worse to class a customer as good when they are bad (5), than it is to class a customer as bad when they are good (1).
Subject Area
Social Science
Instances
1,000
Features
20
Data Types
Multivariate
Tasks
Classification
Feature Types
Categorical, Integer

Features

NameRoleTypeUnitsMissing ValuesDescription

Introductory Paper

Additional Metadata

Keywords
Authors
Hans Hofmann
Year Created
1994
License
CC BY 4.0