Auto Classifier Node

A

AI/ML/Tuning

Automatically finds the best classification model. Cross-validates Naive Bayes, Decision Tree, Logistic Regression, Random Forest and SVM, then retrains the winner on the full dataset. The reported Best Model Type can be fed straight into Grid Search to tune it further.

ai_ml_tuning_auto_classifierml

Inputs7

Outputs4

Security exposure6/10

Packageml

Ratings

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

SecurityAttack surface and exposure impact.

6/10Medium

PrivacyPotential sensitivity of processed data.

6/10Medium

PerformanceRuntime or resource pressure.

4/10Medium

GovernancePolicy, audit, or compliance impact.

7/10High

ReliabilityOperational stability considerations.

8/10High

CostExternal or compute cost impact.

4/10Medium

Input Pins

7

Input

Execution

exec_in

Execution trigger

CV Folds

Integer

cv_folds

Number of cross-validation folds

Default 5

Metric

String

metric

Metric the leaderboard is ranked by. Accuracy is the share of correct rows; Macro F1 averages per-class F1 with equal weight per class, which is the right choice when the classes are imbalanced.

Default accuracy

accuracymacro_f1

Include SVM

Boolean

include_svm

Include SVM in comparison (slower but often more accurate)

Default true

Include Logistic Regression

Boolean

include_logistic

Include Logistic Regression. Fast, and the only candidate that yields calibrated probabilities, but it expects scaled features — fit a Feature Scaler first for a fair comparison.

Default true

Include Random Forest

Boolean

include_random_forest

Include Random Forest. Usually the strongest candidate here, at the cost of training one tree per ensemble member on every fold.

Default true

Data Source

String

source

Data source type

Default Database

Database

Output Pins

4

Done

Execution

exec_out

Activated when AutoML completes

Results

Struct

results

Complete AutoML results with leaderboard

SchemaAutoMLResultAutoMLResultAutoMLResult5 fields

leaderboardArray<AutoMLEntry>required

Leaderboard entries sorted by score

itemsAutoMLEntryarray item

Entry in the AutoML leaderboard

model_typestringrequired

Model type (e.g., "GaussianNaiveBayes", "DecisionTree", "SVM")

best_paramsobjectrequired

Best parameters found for this model

cv_scorenumber:doublerequired

Best CV score achieved

format double

train_time_secsnumber:doublerequired

Training time in seconds

format double

rankinteger:uintrequired

Rank in leaderboard (1 = best)

format uintmin 0

best_model_indexinteger:uintrequired

Index of best model in leaderboard

format uintmin 0

total_models_triedinteger:uintrequired

Total models trained

format uintmin 0

total_time_secsnumber:doublerequired

Total elapsed time in seconds

format double

metricstringrequired

Metric used for optimization

Best Model

Struct

best_model

The best model trained on full data

SchemaNodeMLModelNodeMLModelNodeMLModel1 fields

model_refstringrequired

Schema enforced

Best Model Type

String

best_model_type

Name of the best algorithm

Node Info

Internal name

ai_ml_tuning_auto_classifier

Category

AI/ML/Tuning

Version

2