Computer Science > QUESTIONS & ANSWERS > MATH MA 5790 Predictive Modeling - Michigan Technological University - Assignment 5 Complete Q&A. (All)

MATH MA 5790 Predictive Modeling - Michigan Technological University - Assignment 5 Complete Q&A.

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MATH MA 5790 Predictive Modeling - Michigan Technological University - Assignment 5 1. The hepatic injury data set was described in the introductory chapter and contains 281 unique compounds, ea ... ch of which has been classified as causing no liver damage, mild damage, or severe damage (Fig. 1.2). These compounds were analyzed with 184 biological screens (i.e., experiments) to assess each compound’s effect on a particular biologically relevant target in the body. The larger the value of each of these predictors, the higher the activity of the compound. In addition to biological screens, 192 chemical fingerprint predictors were determined for these compounds. Each of these predictors represent a substructure (i.e., an atom or combination of atoms within the compound) and are either counts of the number of substructures or an indicator of presence or absence of the particular substructure. The objective of this data set is to build a predictive model for hepatic injury so that other compounds can be screened for the likelihood of causing hepatic injury. Start R and use these commands to load the data: (a) Given the classification imbalance in hepatic injury status, describe how you would create a training and testing set. Which classification statistic would you choose to optimize for this exercise and why? [Show More]

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