Found 47 datasets matching "support vector machine".
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Data used in the manuscript submission that describes the use of support vector machine and wavelet decomposition for calibration of a SWAT model of the Illinois River Watershed
Search relevance: 120.19 | Views last month: 0 -
Data used in the manuscript submission that describes the use of support vector machine calibration of a SWAT model of the Illinois River Watershed
Search relevance: 117.63 | Views last month: 4 -
Background We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based...
Search relevance: 69.66 | Views last month: 0 -
To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity,...
Search relevance: 60.91 | Views last month: 0 -
The Multiple Kernel Anomaly Detection (MKAD) algorithm is designed for anomaly detection over a set of files.
Search relevance: 57.26 | Views last month: 1 -
Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to...
Search relevance: 56.93 | Views last month: 0 -
In this paper we propose ν-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark one-class Support Vector...
Search relevance: 55.04 | Views last month: 1 -
In this paper we propose ν-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark one-class Support Vector...
Search relevance: 54.46 | Views last month: 1 -
These data represent the underlying figures and tables of the manuscript. This dataset is associated with the following publication: Yuan, L., and K.J. Forshay. Using SWAT to Evaluate Streamflow...
Search relevance: 54.41 | Views last month: 21 -
This dataset contains surface-ocean partial pressure of carbon dioxide (pCO2) that the ensemble mean of six two-step clustering-regression machine learning methods. The ensemble is a combination...
Search relevance: 54.25 | Views last month: 0 -
In this paper we propose $\nu$-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark one-class Support Vector...
Search relevance: 53.84 | Views last month: 0 -
One-class nu-Support Vector machine (SVMs) learning technique maps the input data into a much higher dimensional space and then uses a small portion of the training data (support vectors) to...
Search relevance: 53.77 | Views last month: 0 -
The data set is composed of inputs and outputs of the DST demonstration and application to risk-based TMDLs and water quality risk assessment in Midwest river basins (Upper Mississippi River, Ohio...
Search relevance: 53.28 | Views last month: 0 -
The estimation of remaining useful life (RUL) of a faulty component is at the center of system prognostics and health management. It gives operators a potent tool in decision making by quantifying...
Search relevance: 53.00 | Views last month: 1 -
This dataset provides estimates of aboveground biomass (AGB) and salt marsh extent in the contiguous United States for 2020 and includes all coastal watersheds across the contiguous United States...
Search relevance: 50.10 | Views last month: 0 -
Damage characterization through wave propagation and scattering is of considerable interest to many non-destructive evaluation techniques. For fiber-reinforced composites, complex waves can be...
Search relevance: 50.00 | Views last month: 0 -
This paper provides a review of three different advanced machine learning algorithms for anomaly detection in continuous data streams from a ground-test firing of a subscale Solid Rocket Motor...
Search relevance: 49.34 | Views last month: 2 -
We use a supervised machine learning strategy to systematically investigate the relative importance of study type, machine learning algorithm, and type of descriptor on predicting in vivo...
Search relevance: 48.87 | Views last month: 0 -
The dataset has all of the information used to create and evaluate 3 independent QSAR models for the fraction of a chemical unbound by plasma protein (Fub) for environmentally relevant chemicals....
Search relevance: 48.10 | Views last month: 20 -
The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation via Particle...
Search relevance: 47.63 | Views last month: 2
