Create a dashboard to compare the performance of various models for prediction:
true positives (TP): These are cases in which we predicted yes (they have the disease), and they do have the disease.
true negatives (TN): We predicted no, and they don't have the disease.
false positives (FP): We predicted yes, but they don't actually have the disease. (Also known as a "Type I error.")
false negatives (FN): We predicted no, but they actually do have the disease. (Also known as a "Type II error.")
The dashboard should be able to load a base search, models are then selected for the prediction of some target variable. Above metrics are recorded as panels comparing the different models.
Create a dashboard to compare the performance of various models for prediction:
The dashboard should be able to load a base search, models are then selected for the prediction of some target variable. Above metrics are recorded as panels comparing the different models.