UCI Machine Learning Repository: Statlog (German Credit Data) Data Set Repository Web Statlog (German Credit Data) Data Set Download:, Abstract: 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 Data Set Characteristics: Multivariate Number of Instances: 1000 Area: Financial Attribute Characteristics: Categorical, Integer Number of Attributes: 20 Date Donated 1994-11-17 Associated Tasks: Classification Missing Values? N/A Number of Web Hits: 355435 Source: Professor Dr. Hans Hofmann Institut f'ur Statistik und 'Okonometrie Universit'at Hamburg FB Wirtschaftswissenschaften Von-Melle-Park 5 2000 Hamburg 13 Data Set Information: 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'. Magix Music Maker 12 Silver Crackle. 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).

Feb 17, 2014 - Open the data/iris.arff Dataset. Click the “Open file” button to open a data set and double click on the “data” directory. Weka provides a number of small common machine learning datasets that you can use to practice on. Select the “iris.arff” file to load the Iris dataset. Weka Explorer Interface with the Iris. Dec 31, 2017 - You can download the actual. Original Data Format arff Name german_credit Version mldata 0 Comment. Description of the German credit dataset. Another older available one is 'German Credit fraud data', which is in ARFF format as used by Weka machine learning. Recent publications: GOTCHA!

1 2 ---------------------------- 1 0 1 ----------------------- 2 5 0 (1 = Good, 2 = Bad) The rows represent the actual classification and the columns the predicted classification. Tony Hawk Proving Ground Download Pc Torrent. 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). Attribute Information: Attribute 1: (qualitative) Status of existing checking account A11.

Arctic Cat Serial Numbers Decoder Online. 1 TUTORIAL M - Profit Analysis of the German Credit Data Using SAS® Enterprise MinerTM 5.3 Guest Author: Chamont Wang, Ph.D. Department of Mathematics and Statistics.