Solar absorptances are often derived from the reflectance values measured with devices which make use of integrating spheres. Instruments of this type can be operated in two different ways, according to whether spectral or integrated reflectances are measured. Though solar absorptances derived from spectral data are inherently more accurate, some commercially available reflectometers are found ...

Experimental MS response factors were measured for 36 different saturated and unsaturated volatile organic compounds (VOC) containing carbon, hydrogen and halogen atoms. Chemical structure was encoded using various molecular descriptors. A quantitative structure-property relationship model was established using the multiple linear regression models. The cross-validation ability of the created m...

We study cross-validation as a scoring criterion for learning dynamic Bayesian network models that generalize well. We argue that cross-validation is more suitable than the Bayesian scoring criterion for one of the most common interpretations of generalization. We confirm this by carrying out an experimental comparison of cross-validation and the Bayesian scoring criterion, as implemented by th...

A cross-validation method based on [Formula: see text] replications of two-fold cross validation is called an [Formula: see text] cross validation. An [Formula: see text] cross validation is used in estimating the generalization error and comparing of algorithms' performance in machine learning. However, the variance of the estimator of the generalization error in [Formula: see text] cross vali...

We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This...

ross-entropy is a measure of the difference between two distribution functions. In order to deal with the divergence of uncertain variables via uncertainty distributions, this paper aims at introducing the concept of cross-entropy for uncertain variables based on uncertain theory, as well as investigating some mathematical properties of this concept. Several practical examples are also provided...

The (relevance) weighted likelihood was introduced to formally embrace a variety of statistical procedures that trade bias for precision. Unlike its classical counterpart, the weighted likelihood combines all relevant information while inheriting many of its desirable features including good asymptotic properties. However, in order to be effective, the weights involved in its construction need ...

In previous researches it can been seen that Bagging, Boosting and Cross-Validation Committee can provide good performance separately. In this paper, Boosting methods are mixed with Bagging and Cross-Validation Committee in order to generate accurate ensembles and take benefit from all these alternatives. In this way, the networks are trained according to the boosting methods but the specific t...

Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potentially, helping to protect against overfitting. Improvements in computational power, recent reductions in the (computational) cost of classification algorithms, and the development of closed-form solutions (for performing ...

In regular statistical models, the leave-one-out cross-validation is asymptotically equivalent to the Akaike information criterion. However, since many learning machines are singular statistical models, the asymptotic behavior of the cross-validation remains unknown. In previous studies, we established the singular learning theory and proposed a widely applicable information criterion, the expe...