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13 Feb 2023: of test data; we trainedon daily snowfall from Jan. ... We do not report results for GPDM on the real data since it was too slow to run on the large test set.

27 Jan 2023: Unlabelled Test Images: 22,000 images. For each training and test image we can store a vector of 240 binary color and texture features. ... about 0.2 sec on this laptop to query 22,000 test images.

19 Nov 2023: Moralisation test for conditional independence. (Lauritzen et al, 1990; Cowell et al, 1999)A. ... directed mixed graphs). • Marginal and conditional independence• Markov boundaries and separation tests for independence• Plate notation.

27 Jan 2023: Once the inversion is done, prediction isO(N ) for thepredictive mean andO(N 2) for the predictive variance per new test case. ... We have demonstrated a significant decrease in test error over the other methods for a givensmall pseudo/active set size.

13 Feb 2023: the density of the actual true test output under the Gaussianpredictive distribution and use its negative log as a measure of loss. ... The training and test data consist of pH values (outputsy of the process) anda control input signal (u).

13 Feb 2023: Initially, a largenumber of features are added, which provides improvements in the test likelihood. ... Table 2 summarises the data and shows thatall approaches had similar test-likelihood performance.

13 Feb 2023: Figure 1 shows the training points, test points, decision boundary from GPCand decision boundary from robust GPC. ... We created 10 pairs of training and test sets by randomlydividing the whole data set into two.

27 Jan 2023: Satellitehas a training set of 4435, a test set of 2000 with 6 classes and 36 variables. ... UCI digit data set has a trainingset of 3823, a test set of 1797, 10 classes and 64 variables.

19 Nov 2023: Constraint-Based Learning: Use statistical tests of marginal and conditionalindependence. Find the set of DAGs whose d-separation relations match theresults of conditional independence tests.

13 Feb 2023: Additionally, for the test set, wemake use of the Negative Log Predictive Probability (NLPP). ... For training we extract 400consecutive data points, while we test on the following 500data points.