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Found 10 papers, 0 papers with code
Vesicoureteral Reflux Detection with Reliable Probabilistic Outputs
Vesicoureteral Reflux (VUR) is a pediatric disorder in which urine flows backwards from the bladder to the upper urinary tract.
Android Malware Detection with Unbiased Confidence Guarantees
We examine its performance on a large-scale dataset collected by installing 1866 malicious and 4816 benign applications on a real android device.
Reliable Probabilistic Classification with Neural Networks
Venn Prediction (VP) is a new machine learning framework for producing well-calibrated probabilistic predictions.
Reliable Prediction Intervals with Regression Neural Networks
This paper proposes an extension to conventional regression Neural Networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence.
Well-calibrated Confidence Measures for Multi-label Text Classification with a Large Number of Labels
We present experimental results using the original and the proposed efficient LP-ICP on two English and one Czech language data-sets.
Guaranteed Coverage Prediction Intervals with Gaussian Process Regression
Gaussian Process Regression (GPR) is a popular regression method, which unlike most Machine Learning techniques, provides estimates of uncertainty for its predictions.
A Cross-Conformal Predictor for Multi-label Classification
Therefore the learning task in this setting is to predict the subset of classes to which each instance belongs.
Regression Conformal Prediction with Nearest Neighbours
A comparison of the predictive regions produced by our measures with those of the typical regression measure suggests that a major improvement in terms of predictive region tightness is achieved by the new measures.
Feature Subset Selection for Software Cost Modelling and Estimation
Feature selection has been recently used in the area of software engineering for improving the accuracy and robustness of software cost models.
Software Effort Estimation with Ridge Regression and Evolutionary Attribute Selection
Software cost estimation is one of the prerequisite managerial activities carried out at the software development initiation stages and also repeated throughout the whole software life-cycle so that amendments to the total cost are made.
