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The results also showed that the VQ technique can decrease the training time and improve prediction performance of the SVR model.
Since analysis of microarray data sets is a high dimensional problem, our results demonstrate that multi-task learning techniques can be employed to improve prediction performance of tumor classification by using redundant genes.
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Several factors can contribute to the improved prediction performance of our approach in predicting RD values from sequences alone.
Incorporation of the AEDI in the ANN model improved prediction performance of the location and scale parameters by 7% and 21%, respectively.
The methodology is independent of the model class, applicable to all black box models, and improves prediction performance for a variety of data in several industrial application areas.
There has been little work on combining PPI datasets with the goal of improving prediction performance for multiple organisms.
Furthermore, associating the information of absorption, signal transduction pathway, physiological agonism/antagonism, or excretion (e.g. half-life) might help improve prediction performance and understand the mechanism of DDIs.
These datasets are used later in this section (see Classification results) to demonstrate that location inter-dependencies can be used to improve prediction performance, even in the absence of PROSITE-based and GO-based features.
To considerably improve prediction performance will require either the development of specific clinical risk algorithms for disease subtypes, such as preterm and term pre-eclampsia, or the addition of biomarkers, or both.
This study also verified the importance of GlobalSoilMap products and a priori pedological information that improved prediction performance and quality of the new FAO soil map of Denmark.
Our model achieved a significantly improved prediction performance in identification of short prokaryotic genes.
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