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374 interactions between 22 diseases and 183 drugs are predicted using our proposed regression model.
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Other variations of the standard relevance network have been suggested (Zhang and Horvath, 2005), and any of these graphs can also be used within our proposed regression methods.
The CIPIC database is used to evaluate the performance of our proposed regression model based on HOPLS.
Our proposed regression model does not require model selection.
Optimum values of the independent parameters were determined by solving a multi-objective optimization problem obtained by using the proposed regression models for dependent parameters.
Analogs of α-tocopherol (compounds D-1 and D-2) have been designed and their antiproliferative activities were evaluated using the proposed regression model.
Based on the QSAR study, novel vitamin-E derivatives (compounds D-1 and D-2) were designed and their antiproliferative activities were evaluated using the proposed regression models.
The codeword of every training point is initialized using a previously proposed regression tree approach.
We used the proposed regression methods to analyze the outcomes infection and infection or death.
The proposed regression models were used to perform the surface response simulations and were useful in selecting suitable materials for constructing the package.
Hence, proposed regression equation can be used for the determination of reduction in load-carrying capacity and bond stress behavior in the real-life structures subjected to different levels of corrosion.
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