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On held-out test data (meaning labeled parses that the model has not seen before), the address parser achieves 99.45% full parse accuracy. For some tasks like named entity recognition it's preferable to use something like an F1 score or variants, mostly because there's a class bias problem...
xarray - xarray (formerly xray) is an open source project and Python package that aims to bring the labeled data power of pandas to the physical sciences, by providing N-dimensional variants of the core pandas data structures. xarray-spatial - Raster-Based Spatial Analysis in Python. YATSM -...
However, it is not easy to collect the representative labeled data involving complex and many physical variables. Generalization has become a major problem that plagues deep learning methods. The second limitation is the interpretability of deep learning methods. Although an ‘end-to-end’ or a ‘...
The training of CNN requires a large number of labeled images. Also, a typical CNN has millions of trainable parameters, making it very efficient in learning the perfect parameters to over-fit the training data42. This limits the generalization ability of the trained model. Data augmentation is...
Research interest in autonomous control of unmanned aerial vehicles (UAVs) has increased rapidly over the past decade. They are now widely used in civilian
6.2. London Underground Map (Criterion R22) This survey was designed to collect some real-world data that reflects the use of knowledge in viewing different London underground maps. It involved sixteen surveyees, twelve at King’s College London (KCL) and four at University of Oxford. Surveyees...
H. An isotope-labeled chemical derivatization method for the quantitation of short-chain fatty acids in human feces by liquid chromatography–tandem mass spectrometry. Anal. Chim. Acta 854, 86–94 (2015). Article CAS PubMed Google Scholar Kiefer, P., Schmitt, U. & Vorholt, J. A. eMZed...
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