Confusion Matrix Node

C

AI/ML/Metrics

Confusion Matrix

Build confusion matrix and calculate precision, recall, and F1 score

ml_eval_confusion_matrixml

Inputs4

Outputs2

Security exposure2/10

Packageml

Ratings

Scores range from 0 to 10. Higher values mean more impact, exposure, or operational weight.

SecurityAttack surface and exposure impact.

2/10High

PrivacyPotential sensitivity of processed data.

2/10High

PerformanceRuntime or resource pressure.

3/10High

GovernancePolicy, audit, or compliance impact.

3/10High

ReliabilityOperational stability considerations.

1/10High

CostExternal or compute cost impact.

1/10High

Input Pins

4

Input

Execution

exec_in

Execution trigger to start confusion matrix calculation

Database

Struct

database

Database connection containing predictions and actuals

SchemaNodeDBConnectionNodeDBConnectionNodeDBConnection1 fields

cache_keystringrequired

Schema enforced

Predictions Column

String

predictions_col

Column name containing predicted values

Default prediction

Actuals Column

String

actuals_col

Column name containing actual/true values

Default target

Output Pins

2

Done

Execution

exec_out

Activated once confusion matrix calculation completes

Result

Struct

result

Confusion matrix with precision, recall, and F1 metrics

SchemaConfusionMatrixResultConfusionMatrixResultConfusionMatrixResult6 fields

matrixArray<Array<integer:int64>>required

2D confusion matrix (rows=actual, cols=predicted)

itemsArray<integer:int64>array item

itemsinteger:int64array item

format int64

labelsArray<string>required

Class labels in order they appear in the matrix

itemsstringarray item

precisionnumber:doublerequired

Weighted average precision across all classes

format double

recallnumber:doublerequired

Weighted average recall across all classes

format double

f1_scorenumber:doublerequired

Weighted average F1 score across all classes

format double

total_samplesinteger:uintrequired

Total number of samples

format uintmin 0

Node Info

Internal name

ml_eval_confusion_matrix

Category

AI/ML/Metrics