In addition, we note that the value of the locality parameter α has little impact on the fit, suggesting that the best predictive features would be a more complex function of the distance.
While the focus of VIDEAN is not on finding the best predictive model, this feature allows the comparison of the predictive capacity of several subsets of descriptors using some baseline methods.
In order to identify which residues contribute to specificity, we developed a computational framework named KINspect, which explores a very large number of combinations of residues, and their contribution toward specificity, and subsequently identifies those featuring the best predictive capability.
Finally, based on the best feature combination, we developed one best predictive model set and applied it to predict the primary tumor sites.
By building in XT9, Swype now features Nuance's best predictive text software but the alternative keyboard also now sports its own personal dictionary.
By confirming that social partner selection is strongly driven by structural, geographical, and topical proximity, we develop a machine-learning social link recommender for individual users trained on a set of features selected as best predictive out of several and we test it on the still widely unexplored domain of a network of interest.
Using logistic regression, we identified clinical features with the best predictive value for a positive methylation abnormality.
Se and Sp were finally used to identify the set of features that yielded best predictive models.
In accordance to this, in a prospective study where clinical examination, TVS, serum markers, and color Doppler, were evaluated in the preoperative investigation of ovarian tumors, the size of the lesion and the TVS morphologic features were the best predictive markers for malignancy in the premenopausal women, and the morphology and CA-125 for the postmenopausal women [ 22].
Of the five biochemical features (H, K, M, P and Co), the hydrophobicity index (H) gave the best predictive performance at 74.70% prediction strength (71.62% sensitivity and 77.79% specificity), MCC = 0.4728 and AUC = 0.8237 (Table 2).
