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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. 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]

  4. Species distribution modelling - Wikipedia

    en.wikipedia.org/wiki/Species_Distribution_Modelling

    The environmental data are most often climate data (e.g. temperature, precipitation), but can include other variables such as soil type, water depth, and land cover. SDMs are used in several research areas in conservation biology , ecology and evolution .

  5. Iris flower data set - Wikipedia

    en.wikipedia.org/wiki/Iris_flower_data_set

    The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]

  6. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).

  7. USDA National Nutrient Database - Wikipedia

    en.wikipedia.org/wiki/USDA_National_Nutrient...

    FoodData Central is USDA's integrated data system that contains five types of data containing information on food and nutrient profiles: [2] Standard Reference, using earlier approaches to determining nutrient profiles of foods in the marketplace, provides a comprehensive list of values for nutrients and food components that are derived from calculations and analyses.

  8. climateprediction.net - Wikipedia

    en.wikipedia.org/wiki/Climateprediction.net

    climateprediction.net (CPDN) is a volunteer computing project to investigate and reduce uncertainties in climate modelling.It aims to do this by running hundreds of thousands of different models (a large climate ensemble) using the donated idle time of ordinary personal computers, thereby leading to a better understanding of how models are affected by small changes in the many parameters known ...

  9. Nutrient depletion - Wikipedia

    en.wikipedia.org/wiki/Nutrient_depletion

    On the level of a complete ecological niche or ecosystem, nutrient depletion can also come about via the loss of the nutrient substrate (soil loss, wetland loss, etc.). Nutrients are usually the first link in the food chain, thus a loss of nutrients in a habitat will affect nutrient cycling and eventually the entire food chain. [2] [3] Nutrient ...