February 2007
Beginner to intermediate
464 pages
16h
English
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 ...
Read now
Unlock full access