3.6. Determining When a New Observation Is Not in a Training Set
Often in drug discovery, a computational model is built for a non-statistician and the user relies on easily understood diagnostics and graphical representations to assess the accuracy of the prediction.
Once a model is in use, a common question asked of the statistician is "how accurate is the prediction?". If the model is providing the user with a quantitative estimates, then the error associated with the prediction can be used to answer this question. This measure takes into account the distance between the new observation and the training set as well as the error in the model. If the model is providing the user with a categorical response and a linear discriminant model is ...
Get Pharmaceutical Statistics Using SAS now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
