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12 Data Sets

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1. Absenteeism at work: The database was created with records of absenteeism at work from July 2007 to July 2010 at a courier company in Brazil.

2. Bank Marketing: The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).

3. Credit Approval: This data concerns credit card applications; good mix of attributes

4. default of credit card clients: This research aimed at the case of customers’ default payments in Taiwan and compares the predictive accuracy of probability of default among six data mining methods.

5. Dow Jones Index: This dataset contains weekly data for the Dow Jones Industrial Index. It has been used in computational investing research.

6. Las Vegas Strip: This dataset includes quantitative and categorical features from online reviews from 21 hotels located in Las Vegas Strip, extracted from TripAdvisor (http://www.tripadvisor.com).

7. Online News Popularity: This dataset summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. The goal is to predict the number of shares in social networks (popularity).

8. Online Shoppers Purchasing Intention Dataset: Of the 12,330 sessions in the dataset, 84.5% (10,422) were negative class samples that did not end with shopping, and the rest (1908) were positive class samples ending with shopping.

9. Polish companies bankruptcy data: The dataset is about bankruptcy prediction of Polish companies.The bankrupt companies were analyzed in the period 2000-2012, while the still operating companies were evaluated from 2007 to 2013.

10. Statlog (Australian Credit Approval): This file concerns credit card applications. This database exists elsewhere in the repository (Credit Screening Database) in a slightly different form

11. Statlog (German Credit Data): 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

12. Wine Quality: Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests (see [Cortez et al., 2009], http://www3.dsi.uminho.pt/pcortez/wine/).


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