Sentence examples for model on dataset from inspiring English sources

The corresponding computation time (average on two machines) on 200 topic model on dataset combination2 is approximately 3 h.

The collections of simulated datasets are then used both (i) to compute by Monte-Carlo method the true global ranking defined in Section 2.5, and (ii) to compute ranking estimates through CV and CSV. Figure 1A displays, for each pair of studies (i, j) in Table 1, the C-index obtained when training a model by Ridge regression on dataset i (rows), and validating that model on dataset j (columns).

We describe our solutions to these two modeling challenges and evaluate several variants of our fully realized model on datasets from the Cognitive Tutor and ASSISTments.

Since the control model and the sequence model required PWM information, performance of these two models on dataset 2 was not presented.

In Table 2, we compare the classification performance of the CSSS method to that of six other models on Dataset II (see Section 2).

We studied whether the model has consistent prediction performance on an independent dataset Testing, by training the model on the dataset Training.

Many such tasks can be posed as convex optimization problems, so algorithms for distributed convex optimization serve as a powerful, general-purpose mechanism for training a wide class of models on datasets too large to process on a single machine.

We trained, test and validate our models on datasets EGFR100 and EGFR1000 datasets and achieved and maximum MCC 0.58 and 0.71 respectively.

Future work should include further development and validation of potential mapping models on datasets with more complete information on covariates and more data on patients with more severe cardiac disease.

Although secondary prevention is similar for both TIA and stroke, basing economic models on datasets which do not distinguish between transient and disabling events, for example, may result in inaccurate cost calculations.

The 10-fold cross validation accuracy of the SMO (sequential minimal optimization) model on training dataset was 0.901, and the accuracy on independent test dataset was 0.895.