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We sought to answer the research question: what factors significantly predict attrition from Whitehall II and what is the most predictive model that can be formed from them?
Then, we analyse points in Γ in order to choose the most predictive model for q.
To build the most predictive model for each dataset, we optimized support vector machine parameters and selected the best number of features (see Fig. 4).
This case is comparable to the algorithm proposed in [28] which selects the most predictive model for the most similar chemical compound of q.
The method selects the most predictive model from the collection of models for a nearest neighbour to the query chemical compound.
We defined an "oracle model" that associates each chemical compound from a given chemical space with the most predictive model from the collection of existing models and we used this model to validate our methods.
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The experimental and predicted growth inhibition patterns obtained by the most predictive models were highly correlated (Supplementary Fig. S11e), with median Spearman's rs values in the 0.53 0.58 range, and 32 out of the 56 drugs from the uncorrelated bioactivities 0.5 dataset had values higher than 0.5 for (Supplementary Fig. S11f).
Diameter 4 yields in general the most predictive models.
Most predictive models are built depending on the decisions made by the organization [17].
The most predictive models included significant main effects for percent sand (as a component of soil texture) and vegetation cover.
Most predictive models are based on a small number of variables collected in cohort studies such as the Framingham Heart Study (D'Agostino et al. 2008).
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