Search results
Results from the WOW.Com Content Network
30+ files (v0.9) CSV Anomaly detection: 2020 (continually updated) [330] [331] Iurii D. Katser and Vyacheslav O. Kozitsin On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature.
Images and (.mat, .txt, and .csv) label files Gender recognition and biometric identification 2017 [45] M Afifi CORe50 Specifically designed for Continuous/Lifelong Learning and Object Recognition, is a collection of more than 500 videos (30fps) of 50 domestic objects belonging to 10 different categories.
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. [1] Such algorithms function by making data-driven predictions or decisions, [2] through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data ...
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 .
This automated quantitative Data-independent acquisition-proteomics software, developed by the Demichev and Ralser labs at the Charité in Berlin, Germany, implements a machine-learning algorithm based on an ensemble of deep neural networks, to boost proteomic depth and reliability of peptide and protein identification. DIA-NN is optimized for ...
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 ...
Digital soil mapping (DSM) in soil science, also referred to as predictive soil mapping [1] or pedometric mapping, is the computer-assisted production of digital maps of soil types and soil properties. Soil mapping, in general, involves the creation and population of spatial soil information by the use of field and laboratory observational ...
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]