Train Classifier (Multinomial Naive Bayes) Node

AI/ML/Classification

Fit/Train a Multinomial Naive Bayes classifier, the standard baseline for text and other count data. Features must be non-negative counts or TF-IDF weights, which is what the Fit TF-IDF Vectorizer node produces. Native multi-class support and a single pass over the data.

fit_multinomial_naive_bayesml

Inputs3

Outputs2

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.

9/10High

GovernancePolicy, audit, or compliance impact.

6/10Medium

ReliabilityOperational stability considerations.

7/10High

CostExternal or compute cost impact.

9/10High

Input Pins

Input

Execution

exec_in

Execution trigger that begins Multinomial Naive Bayes training

Data Source

String

source

Choose which backend supplies the training data

Default Database

Database

Alpha

Float

alpha

Additive (Laplace/Lidstone) smoothing added to every feature count. 1.0 is the usual choice; smaller values trust the training counts more, and 0 disables smoothing so any term unseen in a class makes that class impossible.

Default 1

Range 0 to 100

Output Pins

Done

Execution

exec_out

Activated once training completes

Model

Struct

model

Thread-safe handle to the trained Multinomial Naive Bayes classifier

Schema enforced

Node Info

Internal name: fit_multinomial_naive_bayes
Category: AI/ML/Classification