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

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

    OpenML: [494] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [495] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...

  3. Species distribution modelling - Wikipedia

    en.wikipedia.org/wiki/Species_Distribution_Modelling

    This database system can also project crop yields and evaluate the impact of environmental factors such as climate change on plant growth and suitability. [12] Most niche modelling methods are available in the R packages 'dismo', 'biomod2' and 'mopa'.. Software developers may want to build on the openModeller project.

  4. 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 ...

  5. Nash–Sutcliffe model efficiency coefficient - Wikipedia

    en.wikipedia.org/wiki/Nash–Sutcliffe_model...

    In some applications such as automatic calibration or machine learning, the NSE lower limit of (−∞) creates problems. To eliminate this problem and re-scale the NSE to lie solely within the range of {0,1} normalization, use the following equation that yields a Normalized Nash–Sutcliffe Efficiency (NNSE) [6] [7]

  6. MNIST database - Wikipedia

    en.wikipedia.org/wiki/MNIST_database

    Sample images from MNIST test dataset. The MNIST database (Modified National Institute of Standards and Technology database [1]) is a large database of handwritten digits that is commonly used for training various image processing systems. [2] [3] The database is also widely used for training and testing in the field of machine learning.

  7. Category:Datasets in machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Datasets_in...

    Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; ... Pages in category "Datasets in machine learning"

  8. Water retention curve - Wikipedia

    en.wikipedia.org/wiki/Water_retention_curve

    Water retention curve is the relationship between the water content, θ, and the soil water potential, ψ. The soil moisture curve is characteristic for different types of soil, and is also called the soil moisture characteristic. It is used to predict the soil water storage, water supply to the plants (field capacity) and soil aggregate stability.

  9. Local regression - Wikipedia

    en.wikipedia.org/wiki/Local_regression

    Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.

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