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Audio features of music samples from different locations. Audio features extracted using MARSYAS software. 1,059 Text Geographic classification, clustering 2014 [138] [139] F. Zhou et al. Million Song Dataset Audio features from one million different songs. Audio features extracted. 1M Text Classification, clustering 2011 [140] [141]
It is a dataset of pedestrians in urban environments. Pedestrians are box-wise labeled. Labeled part contains 15560 samples with pedestrians and 6744 samples without. Test set contains 21790 images without labels. Images Object recognition and classification 2006 [53] [54] [55] Daimler AG: CamVid
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
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]
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]
Download QR code; Print/export ... List of datasets for machine-learning research; A. Arabic Speech Corpus; B. ... and test data sets
Google Dataset Search is a search engine from Google that helps researchers locate online data that is freely available for use. [1] The company launched the service on September 5, 2018, and stated that the product was targeted at scientists and data journalists .
t-SNE has been used for visualization in a wide range of applications, including genomics, computer security research, [3] natural language processing, music analysis, [4] cancer research, [5] bioinformatics, [6] geological domain interpretation, [7] [8] [9] and biomedical signal processing.