Chapter 5: Principles of Modeling

Exercise: Confusion Matrix and Class Statistics

1) Read data predicted_income.csv
The "income" column contains people’s actual income class values. The “Prediction (income)” column contains their predicted income class values produced by some classification model based on the other information available in the dataset. The income class has two values: “<=50K” and “>50K”

2) Evaluate the accuracy of the income class prediction using the Scorer (JavaScript) node.
NOTE: this node is part of an extension. If you cannot find it in the Node Repository, search for it on the KNIME Hub. Drag and drop it into the workflow and follow the instructions to install the required extension.
Execute the node, and open the interactive view.
- What is the overall accuracy of the model?

3) Open the configuration dialog of the Scorer (JavaScript) node and exclude the following statistics from the class prediction statistics table:
- True positives
- False positives
- True negatives
- False negatives

4) Open the interactive view again, and display the number of rows in the confusion matrix. What is the number of rows in the dataset?

Confusion_Matrix_Exercise

External resources

Used extensions & nodes

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