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Dataset of legal contracts with rich expert annotations ~13,000 labels CSV and PDF Natural language processing, QnA 2021 The Atticus Project: Vietnamese Image Captioning Dataset (UIT-ViIC) Vietnamese Image Captioning Dataset 19,250 captions for 3,850 images CSV and PDF Natural language processing, Computer vision 2020 [112] Lam et al.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily of images or videos for tasks such as object detection, facial recognition, and multi-label classification.
Download as PDF; Printable version ... Statistical data sets (18 C, 32 P) ... The following 4 pages are in this category, out of 4 total. This list may not reflect ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936). [1]A data set (or dataset) is a collection of data.In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.
The contents of the Comparison of facial image datasets page were merged into List of datasets for machine-learning research on 22:52, 7 March 2016 (UTC). For the contribution history and old versions of the redirected page, please see ; for the discussion at that location, see its talk page.
a list of classifiers f k for k ∈ {1, …, K} Procedure: For each k in {1, …, K} Construct a new label vector z where z i = y i if y i = k and z i = 0 otherwise; Apply L to X, z to obtain f k; Making decisions means applying all classifiers to an unseen sample x and predicting the label k for which the corresponding classifier reports the ...