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Found 1080 dataset(s) matching "class one".
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The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file...
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The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file...
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The study sought to measure knowledge about laws related to domestic violence and harassment, resources for help, rape myths, and skills such as conflict resolution; attitudes about the...
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This HEASARC database table contains information on the so-called "Related Objects" only, as taken from the Catalog of Cataclysmic Binaries, Low-Mass X-ray Binaries, and Related Objects...
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This HEASARC database table contains information on cataclysmic binaries only, as taken from the Catalog of Cataclysmic Binaries, Low-Mass X-ray Binaries, and Related Objects (7th Edition, Release...
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Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Abstract: This article describes the results of applying four unsupervised anomaly detection...
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A supervised learning task involves constructing a mapping from an input data space (normally described by several features) to an output space. A set of training examples---examples with known...
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Data is for three experiments. The first experiment examined calcification effects of ingested microbeads. The second experiment observed ingestion rates of four size classes of microbeads and how...
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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...
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The Multiple Kernel Anomaly Detection (MKAD) algorithm is designed for anomaly detection over a set of files. It combines multiple kernels into a single optimization function using the One Class...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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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...
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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...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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This dataset provides related gridded outputs of future modeled forest carbon sequestration priority and related species richness and habitat suitability for the western United States. The primary...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of...
