1. Online Retail: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. 2. Online Retail II: A real online retail transaction data set of two years. 3. Stock keeping units: The dataset is provided by the “Trialto Latvia LTD”, the third-party logistics operator. Each observation stands for a distinct type of item for sale. 4. Stock keeping units: The dataset is provided by the “Trialto Latvia LTD”, the third-party logistics operator. Each observation stands for a distinct type of item for sale. 5. 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/). 6. Facebook Live Sellers in Thailand: Facebook pages of 10 Thai fashion and cosmetics retail sellers. Posts of a different nature (video, photos, statuses, and links). Engagement metrics consist of comments, shares, and reactions. 7. Iranian Churn Dataset: This dataset is randomly collected from an Iranian telecom company’s database over a period of 12 months. 8. Iranian Churn Dataset: This dataset is randomly collected from an Iranian telecom company’s database over a period of 12 months. 9. clickstream data for online shopping: The dataset contains information on clickstream from online store offering clothing for pregnant women. 10. Productivity Prediction of Garment Employees: This dataset includes important attributes of the garment manufacturing process and the productivity of the employees which had been collected manually and also been validated by the industry experts. 11. 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). 12. 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. 13. Apartment for rent classified: This is a dataset of classified for apartments for rent in USA.
14. in-vehicle coupon recommendation: This data studies whether a person will accept the coupon recommended to him in different driving scenarios 15. 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. 16. 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). 17. 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. 18. Taiwanese Bankruptcy Prediction: The data were collected from the Taiwan Economic Journal for the years 1999 to 2009. Company bankruptcy was defined based on the business regulations of the Taiwan Stock Exchange. 19. CNAE-9: This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a
subset of 9 categories | 
