Global Performance Indicators and Target Statistics
Global performance indicators:
- Predictive power measures the accuracy of the predictive model. It takes a value between 0% and 100%. This value must be as close as possible to 100%, without being equal to 100%.
- Predictive confidence indicates the capacity of your predictive model to achieve the same degree of accuracy when you apply it to a new data set, which has the same characteristics as the training data set. Prediction confidence takes a value between 0% and 100%. This value must be as close as possible to 100%.
Target statistics:
Gives the frequency (%) of the two target categories, in this case 1 and 0, in the training and validation subsets.
![The Global Performance Indicators and Target Statistics for the overview report in a classification model. The Global Performance Indicators and Target Statistics for the overview report in a classification model.](/service/media/topic/b01efc09-bc7e-477d-99ff-f0778c5f3929/SACR21_39_en-US_media/SACR21_39_en-US_images/SACR21_CM_Analysis_01.png)
Influencer Contributions and % Detected Target
Influencer Contributions:
Shows the relative importance of each variable used in the predictive model. It examines the influence on the target of the top five variables used in the predictive model. It's a useful report to spot if there are leaker variables in a model, as the leaker has a suspiciously high contribution, overwhelming all of the other variables.
% Detected Target:
Compares the classification model performance (on the validation subsample of the data) to a random model and a hypothetically perfect (100% accurate) model.
The % detected target curve compares the model to the hypothetically perfect and random models. It shows the percentage of the total population (x-axis) that corresponds to the % of positive detected targets (y-axis) given by the classification model.
- If the model was perfectly accurate, then the blue model curve would overlap the green perfect model curve. Predictive power = 100%.
- If the model was perfectly inaccurate, then the blue model curve would overlap the red random curve. Predictive power = 0%.
![The Influencer Contributions and % detected target for the overview report in a classification model. The Influencer Contributions and % detected target for the overview report in a classification model.](/service/media/topic/b01efc09-bc7e-477d-99ff-f0778c5f3929/SACR21_39_en-US_media/SACR21_39_en-US_images/SACR21_CM_Analysis_01.1.png)