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Consistent with unsupervised clustering, PR-dependent genes were predictive of whether a particular sample was non-malignant FTE or HGSC (as indicated by a high sample prediction accuracy for each list using dataset A, total n=37 samples).
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In conclusion, we can state that for the data sets examined in this paper out-of-sample prediction accuracy amounts to broadly 25%%.
The PPO model is compared to ordinal and multinomial response models on the basis of adequacy of model fit, significance of covariates, and out-of-sample prediction accuracy.
Prediction accuracy in these bi-parental populations reached around 0.4 at most, when 90 individuals were randomly taken (50 times) as the training population from the entire sample of bi-parental population 2. When 50 individuals were sampled, prediction accuracy dropped to around 0.3.
The size of negative sample set was the same as the positive sample; the prediction accuracy in Table 2 was simply the percentage of correct predictions among both positive and negative samples.
The determination of the time-to-next glucose sample utilizes prediction accuracy.
The model successfully predicted radiation types for 23 out of 24 samples, a prediction accuracy of 96%.
Only 4 out of the 10,000 samples achieved prediction accuracy greater than or equal to 0.81 (accuracy for the 21 genes using the Random Forest classifier).
For a large sample size, prediction accuracies from penalized methods are expected to be similar to that from ridge [ 23, 35, 50].
In the training sample set, the accuracy of the SVM is higher than in the BP neural network; in the test sample set, the prediction accuracy of the SVM model increased by 2.79 %, while the prediction accuracy of the BP neural network declined by16.66 %.
The effects of sample size on prediction accuracy are clear.
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CEO of Professional Science Editing for Scientists @ prosciediting.com