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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 ...
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]
Users can access global climate and environmental datasets or upload their own data, perform data analysis across six different experiment types with a suite of 17 different methods, and easily visualize, interpret and evaluate the results of the models.
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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]
The Water Erosion Prediction Project (WEPP) model is a physically based erosion simulation model built on the fundamentals of hydrology, plant science, hydraulics, and erosion mechanics. [ 1 ] [ 2 ] The model was developed by an interagency team of scientists to replace the Universal Soil Loss Equation (USLE) and has been widely used in the ...
The European Soil Database is the only harmonized soil database in Europe from which many other data information and services are derived. For instance, the European Soil Database v2 Raster Library contains raster (grid) data files with cell sizes of 1 km x 1 km for a large number of soil related parameters. Each grid is aligned with the ...
SWAT (soil and water assessment tool) is a river basin scale model developed to quantify the impact of land management practices in large, complex watersheds. SWAT is a public domain software enabled model actively supported by the USDA Agricultural Research Service at the Blackland Research & Extension Center in Temple, Texas , USA. [ 1 ]