instance based learning methods
Experiments in Graph Based Semi Supervised Learning Methods for Class Instance Acquisition
... For instance, the Freebase-1 graph has a high average degree of ...3). Based on this, we suggest that average degree, an easily computable struc- tural property of the graph, may be a useful indica- tor in ...
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Learning Instance-Specific Predictive Models
... population-wide methods, the next two are examples of instance-specific methods, and AB is an ensemble ...test instance that is then used to classify it, and is an example of a ...
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Statistical Data Classification Using Instance Based Learning Algorithm
... For similarity measure the K most similar instances are used. K most similar instances can be collected with similarity measure for a given hidden instance. For all instances this is the simple way to determine ...
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Effective News Video Classification Based On Audio Content: A Multiple Instance Learning Approach
... the instance labels within the ...labelled instance and for a negatively labelled bag, all instances are known to have negative ...the methods used for extraction of audio features and MIL ...
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Horror image recognition based on context aware multi instance learning
... experience. Methods in the machine learning-based category involve the training of mapping functions between low-level features and high-level emotional semantics in a “black box” ...classifier ...
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Multiple-Instance Learning from Distributions
... multiple-instance learning (MIL) ...a learning algorithm in the form of la- beled sets, or “bags,” of ...accurate instance- and bag-labeling functions in this setting as well as functions that ...
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Multi view multi instance learning based on joint sparse representation and multi view dictionary learning
... slightly lower than that of the EC-SVM method. However, the M 2 IL outperforms the existing methods with obvious performance improvements on the other 19 categories. The higher AUC values (larger than 90) of ...
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Residual uncertainty estimation using instance based learning with applications to hydrologic forecasting
... These methods usually do not discriminate between different sources of un- ...Post-processing methods assume the exis- tence of a single calibrated model with an optimal set of model parameters, and build a ...
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C PNN: Multiple instance Learning Based on Clustering and Probabilistic Neural Network
... single-instance learning(SIL) and multiple-instance learning(MIL), many traditional learning methods such as nearest neighbor classification, SVM and other classification ...
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Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application
... developed based on many of the paradigms in machine learning such as support vector machines (Andrews et ...one instance has a positive ...decision based on each instance (pattern) as ...
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Localized instance fusion of MRI data of Alzheimer’s disease for classification based on instance transfer ensemble learning
... by instance transfer learning algorithm (ITL) based on wrapper mode, thereby obtaining optimal transferred domain ...by instance trans- fer learning, thereby being helpful for the small ...
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Multi-Instance Learning with Any Hypothesis Class
... PAC- learning algorithm for MIL with APRs, and this algorithm is polynomial in both the size of the bag and the dimension of the Euclidean space, then it is possible to polynomially PAC-learn DNF formulas, a ...
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Multiple Instance Learning of Real Valued Data
... three methods for learning axis-aligned boxes (often referred to as APR for axis-parallel rectangles) in the multiple-instance ...for learning axis-aligned boxes in the multi-instance ...
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International Journal of Movement Education and Social Science
... of learning in the digital age and the pedagogies that support learners in acquiring new competencies and skills to tackle current age ...pedagogical methods while designing e- learning systems to ...
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Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization
... performs the latter two, which only use limited types of relations between objects. This fact shows the importance of accounting for multi-type relations in M3L. M3Lcmf has a lower 1-RankLoss but a higher AvgRecall and ...
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Using Project based Learning in Writing an Educational Article: An Experience Report
... Based on the chart Chamberland et al. above, every individual in the classroom treated as individuals with the knowledge different so that the lecturer gives great opportunities on any interest in knowledge. No ...
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SMALL GROUP LEARNING METHODS AND THEIR EFFECT ON LEARNERS’ RELATIONSHIPS
... cooperative learning are not automatic, however, and if imperfectly implemented, the method can create considerable difficulties for educators, most notably dysfunctional teams and student resistance or hostility ...
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OILSW: A New System for Ontology Instance Learning
... Abstract. The Semantic Web is expected to extend the current Web by providing structured content via the addition of annotations. Because of the large amount of pages in the Web, manual annotation is very time consuming. ...
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Convex and Scalable Weakly Labeled SVMs
... In traditional MIL, a bag is labeled positive when it contains at least one positive instance, and is labeled negative otherwise. Although the bag labels are often available, the instance labels are only ...
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Searching for Active Learning Methods for New Product Development Purposes
... Peer led team learning (PLTL) is a method with the particularity that students lead the groups. They are re- cruited and trained for this role. They lead groups of six to eight classmates during workshops, solving ...
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