1.
Quality Control
Predictive Analytics Use Case

2.
Quality Control
Sample Application
Description
• Businesses that fail to control quality will lose customers
and market share and, in some cases, expose the
organization to legal risk and liability. Predictive quality
control is define to maintain red wine quality by observing
effective factors of wine.

3.
Target
Quality Category
Quality Control
Sample Application

4.
• Effecting factors of wine quality such as acid,
sulphates residual sugar, chlorides.
• Other influencing components - density, PH, alcohol
level etc.
Influencing
Factors
Quality Control
Sample Application

5.
Classification is the method used for classifying numeric
and/or categorical data into two groups based on
predefined categories.
• Higher classification accuracy (>=70%) means the results
are reliable and accurate.
• Lower classification accuracy (<70%) means the model
needs to be rebuilt using different input parameters.
Algorithm(s)
Quality Control
Sample Application

6.
Training
dataset
Quality Control
Sample Application

7.
Testing
dataset
Quality Control
Sample Application

8.
Model
Visualization
Quality Control
Sample Application

9.
Model
Visualization
Quality Control
Sample Application

10.
Model
Summary
Quality Control
Sample Application

11.
Interpretation
Quality Control
Sample Application

12.
Simulation
Quality Control
Sample Application

13.
Result
• Flag containing Quality category information with ‘High’
and ‘Low’ values.
Quality Control
Sample Application

14.
Single Apply
To predict Quality of Red wine, we carried out using APPLY
functionality shown below.
Quality Control
Sample Application

15.
Result
Quality Control
Sample Application

16.
Prediction
• Comparison of predicted quality category and actual quality
category
Quality Control
Sample Application

17.
Prediction
Accuracy
Predicted Values
Actual
Values
• Prediction Accuracy is: 43.95 %
Quality Control
Sample Application

18.
Quality Control
Predictive Analytics Use Case
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Smarten – Quality Control Use Case - 2020