Train Clustering (KMeans) Node

AI/ML/Clustering

Train Clustering (KMeans)

Fit/Train KMeans Clustering

fit_kmeansml

Inputs3

Outputs2

Security exposure4/10

Packageml

Ratings

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

SecurityAttack surface and exposure impact.

4/10Medium

PrivacyPotential sensitivity of processed data.

4/10Medium

PerformanceRuntime or resource pressure.

4/10Medium

GovernancePolicy, audit, or compliance impact.

4/10Medium

ReliabilityOperational stability considerations.

3/10High

CostExternal or compute cost impact.

3/10High

Input Pins

Input

Execution

exec_in

Execution trigger that begins clustering

Cluster

Integer

cluster

Choose how many centroids to fit

Default 2

Range 1 to 100

Data Source

String

source

Choose which backend supplies the training data

Default Database

Database

Output Pins

Done

Execution

exec_out

Activated once training completes

Model

Struct

model

Thread-safe handle to the trained KMeans model

Schema enforced

Node Info

Internal name: fit_kmeans
Category: AI/ML/Clustering