[PDF] Top 20 Cost-Sensitive Learning to Rank
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Cost-Sensitive Learning to Rank
... could rank potential outages for the next storm so high damage outages can be ...as cost-sensitive ranking, problems of maximizing a company’s cost-saving via a ranking ... See full document
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A COST SENSITIVE LEARNING METHOD TO TUNE THE NEAREST NEIGHBOUR FOR INTRUSION DETECTION
... novel cost-sensitive learning algorithm is proposed to improve the performance of the nearest neighbor for intrusion ...the learning algorithm is to minimize the total cost in ... See full document
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Learning cost sensitive Bayesian networks via direct and indirect methods
... on cost-sensitive learning ...for learning cost-sensitive Bayesian networks: one by using a direct approach that amends an algorithm and a second that uses an indirect approach ... See full document
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Is Learning to Rank Worth it? A Statistical Analysis of Learning to Rank Methods in the LETOR Benchmarks
... After almost a decade of research and development of L2R algorithms, we have here raised two controversial but important questions that should be further discussed by the Information Retrieval community. First, given all ... See full document
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Scaling Learning to Rank to Big Data: Using MapReduce to parallelise Learning to Rank
... the cost of being more computationally expensive per ...the cost of higher per-iteration computational costs is L- BFGS [ 134 ], or any other quasi-Newton optimisation ...of Learning to Rank ... See full document
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Software Defect Prediction Using Enhanced Machine Learning Technique
... machine learning applications for ...novel cost sensitive algorithms cost sensitive variance score, cost sensitive laplacian score and cost sensitive ... See full document
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Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
... When the model set includes the true posterior, the threshold-shifted ML approach is optimal. This naturally brings us to the following question: why not employ a rich model set (for example, a multi-layer neural ... See full document
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Cost Sensitive Class Imbalance Learning using ANFIS
... In cost sensitive neural networks the cost is included in learning rate, error computation and weight ...1)Decrease learning rate for costly examples 2) Include penalty factor for error ... See full document
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Efficient learning of Arrhythmia data set with Multi class cost sensitive classifiers
... of cost-sensitive classification is medical diagnosis, where a doctor would like to balance the costs of various possible medical tests with the expected benefits of the tests for the ...monetary ... See full document
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Learning to Rank Lexical Substitutions
... a learning task like the LexSub task: most features are relatively weak pre- dictors on their own, and we can learn from a large number of data points (2000 sentences with an av- erage set size of 20, about 40K ... See full document
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An overview of classification algorithms for imbalanced datasets
... a cost- sensitive learning algorithm, so that the amount of discarded training data is ...a cost-sensitive learning algorithm is that misclassification costs are often ...a ... See full document
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A cost sensitive decision tree learning algorithm based on a multi armed bandit framework
... 5 Cost-sensitive learning could be thought of as involving two decision-makers because there is an algorithm and costs which sometimes work together well and sometimes do ...for ... See full document
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Improving specific class mapping from remotely sensed data by cost sensitive learning
... Learning with an imbalanced data set is one of the most challenging problems in many real-world applications and it has been recognised as a crucial problem in machine learning and data mining (Cao et al. ... See full document
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Cost-sensitive adaboost algorithm for ordinal regression based on extreme learning machine
... IEEE TRANSACTIONS ON CYBERNETICS 1 A Cost-Sensitive AdaBoost algorithm for Ordinal Regression based on Extreme Learning Machine Annalisa Riccardi, Francisco Fern´andez-Navarro, Member IE[r] ... See full document
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Online Active Learning Classification on the Basis Misclassification Error
... of cost-sensitive ...misclassification cost walk takes cost into accordingly directly depth mixture bit [1], [2], ...for cost-sensitive group in creative writings [9], ...the ... See full document
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Cost sensitive decision tree learning using a multi armed bandit framework
... and cost would result in a large number of classes, it was decided that three for each measurement would be more advisable rather than four each as the resulting combination would mean too many ...the cost ... See full document
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Cost sensitive Bayesian network learning using sampling
... size, then estimates each example in the same sample size by voting each example in different samples, where the number of instances in each resamples is smaller than the training size, and then applies an equation (1) ... See full document
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A Comparison of Models for Cost Sensitive Active Learning
... Active Learning (AL) is a selective sam- pling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ...data, cost ... See full document
9
Cost-Sensitive Learning with Noisy Labels
... In order to more clearly understand the impact of label noise, it is useful to consider a more natural and simpler formalism for label noise, where a random noise process cor- rupts the labels (Biggio et al., 2011), ... See full document
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Active Learning for Cost-Sensitive Classification
... active learning algorithm for CSMC called Cost Over- lapped Active Learning ( COAL ...large cost range, akin to uncertainty-based approaches in active regres- sion (Castro et ...smallest ... See full document
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