Irvine, CA: University of California, School of Information and Computer Science Usage: Predict the risk score by features, using regression or multivariate classification. A value of +3 indicates that the auto is risky, and a value of -3 that it is probably safe. It is then adjusted for actual risk in a process known to actuaries as symboling.

Information about automobiles by make and model, including the price, features such as the number of cylinders and MPG, as well as an insurance risk score.The risk score is initially associated with auto price. airport, providing the airport ID number and name along with the location city and state. airport codes.This dataset contains one row for each U.S. Related Research: Kohavi, R., Becker, B., (1996). Usage: Classify people using demographics to predict whether a person earns over 50K a year. Datasets Dataset nameĪdult Census Income Binary Classification datasetĪ subset of the 1994 Census database, using working adults over the age of 16 with an adjusted income index of > 100. You can find this in the module palette to the left of the experiment canvas in Machine Learning Studio (classic).You can use any of these datasets in your own experiment by dragging it to your experiment canvas. The rest of these sample datasets are available in your workspace under Saved Datasets. By using Kaggle, you agree to our use of cookies. We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Please note that the test data must also contain target values. The file settings.txt contains the dataset name of train and test set and the name of the target column. For example when the value '?' Occur in the data section and it is not defined for this attribute, the data-readin would fail. If using this code, please quote: BMC Bioinformatics, EnzML: multi-label prediction of enzyme classes using InterPro signatures, Luna De Ferrari, Stuart Aitken, Jano van. A Java harness to load data from database, create Weka ARFF and Mulan ARFF+XML files, run machine learning experiments and save the evaluation and predictions to database. German Credit Data Set 1) Install WEKE then 2) Download the German credit data set, save the file with the.arff format then make the experiments as per your syllabus.

German credit data set arff rescue