List of datasets in computer vision and image processing
Outline of machine learning
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Structured prediction or structured (output) learning is an umbrella term for supervised machine learning techniques that involves predicting structured objects, rather than scalar discrete or real values.[1]
Similar to commonly used supervised learning techniques, structured prediction models are typically trained by means of observed data in which the true prediction value is used to adjust model parameters. Due to the complexity of the model and the interrelations of predicted variables the process of prediction using a trained model and of training itself is often computationally infeasible and approximate inference and learning methods are used.
^Gökhan BakIr, Ben Taskar, Thomas Hofmann, Bernhard Schölkopf, Alex Smola and SVN Vishwanathan (2007), Predicting Structured Data, MIT Press.
and 23 Related for: Structured prediction information
predicting structured objects, rather than scalar discrete or real values. Similar to commonly used supervised learning techniques, structuredprediction models...
Protein structureprediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its...
This list of protein structureprediction software summarizes notable used software tools in protein structureprediction, including homology modeling...
Secondary structureprediction is a set of techniques in bioinformatics that aim to predict the secondary structures of proteins and nucleic acid sequences...
Crystal structureprediction (CSP) is the calculation of the crystal structures of solids from first principles. Reliable methods of predicting the crystal...
A prediction (Latin præ-, "before," and dictum, "something said") or forecast is a statement about a future event or about future data. Predictions are...
Critical Assessment of StructurePrediction (CASP), sometimes called Critical Assessment of Protein StructurePrediction, is a community-wide, worldwide...
flexibility in being applied to a wide variety of tasks, including structuredprediction problems. It is not clear that SVMs have better predictive performance...
This list of RNA structureprediction software is a compilation of software tools and web portals used for RNA structureprediction. The single sequence...
applied in pattern recognition and machine learning and used for structuredprediction. Whereas a classifier predicts a label for a single sample without...
(2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. ISBN 978-0-387-84884-6. "Gradient Descent, the Learning Rate...
scenario that combines semi-supervised learning with active learning. Structuredprediction: When the desired output value is a complex object, such as a parse...
geometry into the prediction of protein structures. Wrinch demonstrated this with the Cyclol model, the first prediction of the structure of a globular protein...
conceptually distinct purposes. First, regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field...
a hypothesis space to find a suitable hypothesis that will make good predictions with a particular problem. Even if the hypothesis space contains hypotheses...
decades. Linus Pauling is credited with the successful prediction of regular protein secondary structures based on hydrogen bonding, an idea first put forth...
maintain a sort of state, allowing it to perform such tasks as sequence-prediction that are beyond the power of a standard multilayer perceptron. Jordan...
such as data engineering, data exploration and model interpretation and prediction. Automated machine learning can target various stages of the machine learning...
model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random...
class selected by most trees. For regression tasks, the mean or average prediction of the individual trees is returned. Random decision forests correct for...
recursively over a structured input, to produce a structuredprediction over variable-size input structures, or a scalar prediction on it, by traversing...
original training set, and must learn to distinguish these two classes. At prediction time, a voting scheme is applied: all K (K − 1) / 2 classifiers are applied...
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