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  2. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    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]

  3. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    5 data sets that center around robotic failure to execute common tasks. Integer valued features such as torque and other sensor measurements. 463 Text Classification 1999 [206] L. Seabra et al. Pittsburgh Bridges Dataset Design description is given in terms of several properties of various bridges. Various bridge features are given. 108 Text

  4. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    THz and thermal video data set This multispectral data set includes terahertz, thermal, visual, near infrared, and three-dimensional videos of objects hidden under people's clothes. 3D lookup tables are provided that allow you to project images onto 3D point clouds. More than 20 videos.

  5. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    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 ...

  6. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

  7. List comprehension - Wikipedia

    en.wikipedia.org/wiki/List_comprehension

    Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.

  8. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    Extended MNIST (EMNIST) is a newer dataset developed and released by NIST to be the (final) successor to MNIST. [ 15 ] [ 16 ] MNIST included images only of handwritten digits. EMNIST includes all the images from NIST Special Database 19 (SD 19), which is a large database of 814,255 handwritten uppercase and lower case letters and digits.

  9. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while remaining concise enough to be mined within an acceptable time limit. A common source for data is a data mart or data ...