Icon

04_​Topic_​Modeling_​LDA_​K_​Optimization

Topic Modeling with LDA: Optimizing K via a Verified Component

The Topic Scorer (Labs) verified component implements an experimental score for semantic coherence, exclusivity and similarity/distance of topics of one or multiple models.

As K increases trends can be found using these scores and a decision for the optimal K can be used. Usually it is a tradeoff between those metrics. Read more on the Verified Components descriptions.

Topic Modeling with LDA: Optimizing K via a Verified Component The Topic Scorer (Labs) verified component implements an experimental score for semantic coherence, exclusivity and similarity/distance of topics of one or multiple models. As K increases trends can be found using these scores and a decision for the optimal K can be used. Usually it is a tradeoff between those metrics. Read more on the Verified Components descriptions. TripAdvisor hotels reviewsright click to open chartskadd model idPerplexity Strings To Document Excel Reader View Exclusivityand Coherence by K Parameter OptimizationLoop Start Loop End GroupBy ConstantValue Column DocumentPreprocessing Topic Extractor(Parallel LDA) Topic Scorer (Labs) ConstantValue Column Math Formula Top k Selector Column Appender Topic Modeling with LDA: Optimizing K via a Verified Component The Topic Scorer (Labs) verified component implements an experimental score for semantic coherence, exclusivity and similarity/distance of topics of one or multiple models. As K increases trends can be found using these scores and a decision for the optimal K can be used. Usually it is a tradeoff between those metrics. Read more on the Verified Components descriptions. TripAdvisor hotels reviewsright click to open chartskadd model idPerplexity Strings To Document Excel Reader View Exclusivityand Coherence by K Parameter OptimizationLoop Start Loop End GroupBy ConstantValue Column DocumentPreprocessing Topic Extractor(Parallel LDA) Topic Scorer (Labs) ConstantValue Column Math Formula Top k Selector Column Appender

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Paolo Tamagnini
Created at: 2023-05-02
On NodePit since: 2023-07-06
Last update: 2024-04-28
Created with KNIME version: v4.7.4
Tags: topicldasemantic coherencecoherenceexclusivityfrextopic modelingverified component

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!