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Analyze the performance indicators of the two classification algorithm on the verification set.

 

How-To-Use:

The input of this node is the predicted result of the model and the true target value (dependent variable). There are at least three columns of data in the data set. After setting the performance evaluation node of the two-class model, you can view the performance indicators (accuracy, recall, F1-score) by connecting the table view; connecting the picture view to view the ROC curve.

 

Precautions:

[True Value], [Predicted Value], and [Predicted Probability] can only select one column respectively.

[Positive label] must exist in the target column.

❖Configuration

After adding the Bi-classifier Evaluation node to the experiment, you can set the Bi-classifier Evaluation node through the "Configuration" page on the right.

[Positive label] Please fill in None or the positive label in the target column (integer or text).

[Reserved digits of performance index] When the rounding precision is positive, the digits after the decimal point are retained; when the rounding precision is negative, the digits before the decimal point are retained.

[Real Value] Select the true value field of the pre-data node.

[Predicted value] Select the forecast value field in the forecast result.

[Predicted Probability] Select the probability field of the generated positive label.

Right-click menu of bi-classifier evaluation:

❖Run Bi-classifier Evaluation Node

Run the node, pass the data to DM-Engine for calculation, and get the output result.

 

❖Reset Bi-classifier Evaluation Node

The node that has been running is reset, the returned result is deleted, and the node status is changed to not running.

 

❖Rename Bi-classifier Evaluation Node

In the right-click menu of the Bi-classifier Evaluation node, select "Rename" to rename the node.

 

❖Refresh Bi-classifier Evaluation Node

In the right-click menu of the Bi-classifier Evaluation node, select "Refresh" to update the synchronization data or parameter information.

 

❖Save as Composite Node

In the right-click menu of the Bi-classifier Evaluation node, select "Save as Composite Node",The selected node can be saved as a composite node to realize a multiplexing node, and the parameters of the saved node are consistent with the original node.

 

❖Cut Bi-classifier Evaluation Node

In the right-click menu of the Bi-classifier Evaluation node, select "Cut" to realize node cutting operation.

 

❖Copy Bi-classifier Evaluation Node

In the right-click menu of the Bi-classifier Evaluation node, select "Copy" to realize node  replication operation.

 

❖Delete Bi-classifier Evaluation Node

In the right-click menu of a Bi-classifier Evaluation node, select "Delete" or click the delete key on the keyboard to delete the node and its input and output connections.