Sentence examples for prediction and evaluate the from inspiring English sources

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Therefore, it is necessary to measure the accuracy of neighborhood prediction and evaluate the effectiveness of our prediction schemes.

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Therefore, energy and carbon models which can undertake predictions and evaluate the potential of different energy efficiency and renewable energy interventions for the housing stock are essential for implementation of these policies and initiatives (Cheng and Steemers 2011).

In case of polyp configuration and grading, ordinal regression analysis was employed, with factors of expression level of different mucins, tumor site, and gender included, in order to generate predictions and evaluate the importance of mentioned predictor variables.

Therefore, the research questions this paper is concerned with are: examining the possibility of predicting scores of final exams as a measure of learning performance, using information collected during the learning progress, identifying the learning activity metrics necessary for the prediction, and evaluating the effectiveness of note taking instruction.

To measure how the GBA genes collectively contribute to the disease, we used them to build prediction models and evaluate the performance in 10-fold cross-validation (CV).

To further validate the relationship between spatial gene-gene interactions, we used the known gene function of the interacting genes of a target gene to predict its function and evaluate the prediction accuracy.

I get students to compare the predictions to reality and evaluate the budget by looking at how it does and doesn't achieve the objectives.

Our method, CvManGO (Computational versus Manual GO annotations), pairs literature-based GO annotations with computational GO predictions and evaluates the relationship of the two terms within GO, looking for instances of discrepancy.

The ROC curve can provide a graphical representation of the relationship between the true-positive and false-positive prediction rate of a model, and evaluate the metrics of its performance.

These data are then divided into training, fine-tuning, and testing sets that are used to train and evaluate the prediction model.

To investigate the effect of unequally lenient strategy on the performance of detecting conserved protein complexes, we vary the two parameters ranging from 2 to 3 and evaluate the prediction accuracy of UEDAMAlign when utilizing known protein complexes or Coach to partition the input PPI networks.

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