WebThe data set contains 3 classes of 50 instances each, % where each class refers to a type of iris plant. One class is. % separable from each other. % --- Predicted attribute: class of iris plant. % --- This is an exceedingly simple domain. % 5. Number of Instances: 150 (50 in each of three classes) % 6. WebBelow are some sample WEKA data sets, in arff format. contact-lens.arff; cpu.arff; cpu.with-vendor.arff; diabetes.arff; glass.arff; ionospehre.arff; iris.arff; labor.arff; ReutersCorn …
GitHub - renatopp/arff-datasets: The collection of ARFF …
WebThe ELF reader for ARFF files supports only categorical features, where all entries are defined in the attribute section. ... The ARFF reader works for the following datasets from UCI WEKA datasets (first jar file from this page). We have a preconfigured directory with arff files here. anneal.arff; balance-scale.arff; credit-g.arff; WebNew Dataset. emoji_events. New Competition. post_facebook. Share via Facebook. post_twitter. Share via Twitter. post_linkedin. Share via LinkedIn. add. New notebook. bookmark_border. ... New Notebook file_download Download (319 B) more_vert. weather-nominal. weather-nominal. Data Card. Code (4) Discussion (0) About Dataset. No … adrian cole st kilda
MOA - Massive Online Analysis download SourceForge.net
WebARFF files have two distinct sections. The first section is the Header information, which is followed the Data information. The Header of the ARFF file contains the name of the relation, a list of the attributes (the columns in the data), and their types. An example header on the standard IRIS dataset looks like this: % 1. WebDownload Open Datasets on 1000s of Projects + Share Projects on One Platform. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. Flexible Data … WebDec 31, 2011 · Download MOA - Massive Online Analysis for free. Big Data Stream Analytics Framework. A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. adrian cochrane cayman