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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 can be modified by options to the doctest runner. In addition, doctest has been integrated with the Python unit test module allowing doctests to be run as standard unittest testcases. Unittest testcase runners allow more options when running tests such as the reporting of test statistics such as tests passed, and failed.
Samples hand-labeled as positive or negative. 2000 Text Classification 2014 [53] [54] N. Abdulla Buzz in Social Media Dataset Data from Twitter and Tom's Hardware. This dataset focuses on specific buzz topics being discussed on those sites. Data is windowed so that the user can attempt to predict the events leading up to social media buzz ...
It is a common pattern in software testing to send values through test functions and check for correct output. In many cases, in order to thoroughly test functionalities, one needs to test multiple sets of input/output, and writing such cases separately would cause duplicate code as most of the actions would remain the same, only differing in input/output values.
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 ...
The Wald–Wolfowitz runs test (or simply runs test), named after statisticians Abraham Wald and Jacob Wolfowitz is a non-parametric statistical test that checks a randomness hypothesis for a two-valued data sequence. More precisely, it can be used to test the hypothesis that the elements of the sequence are mutually independent.
Test data can be generated by the tester or by a program or function that assists the tester. It can be recorded for reuse or used only once. Test data may be created manually, using data generation tools (often based on randomness), [4] or retrieved from an existing production environment. The data set may consist of synthetic (fake) data, but ...
Employment testing is the practice of administering written, oral, or other tests as a means of determining the suitability or desirability of a job applicant. The premise is that if scores on a test correlate with job performance , then it is economically useful for the employer to select employees based on scores from that test.