Clustering VIs

LabVIEW 2018 Analytics and Machine Learning Toolkit Help

Edition Date: July 2018

Part Number: 377059B-01

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Owning Palette: Analytics and Machine Learning VIs

Requires: Analytics and Machine Learning Toolkit. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.

Use the Clustering VIs to initialize, train, evaluate, and deploy clustering models that group data items into clusters. Data items in the same cluster share more similarities than those in other clusters.

Palette ObjectDescription
Deploy Clustering ModelDeploys a trained model and returns predicted labels of input data.
Evaluate Clustering ModelEvaluates a trained clustering model with training data or new test data.
Initialize Clustering Model (DBSCAN)Initializes the hyperparameters of the density-based spatial clustering of applications with noise (DBSCAN) algorithm. You can either directly set the hyperparameters or specify multiple values for each hyperparameter. If you specify multiple values for each hyperparameter, the Train Clustering Model VI uses grid search to find the optimal set of hyperparameters.
Initialize Clustering Model (GMM)Initializes the hyperparameters of the Gaussian mixture model (GMM) algorithm. You can either directly set the hyperparameters or specify multiple values for each hyperparameter. If you specify multiple values for each hyperparameter, the Train Clustering Model VI uses grid search to find the optimal set of hyperparameters.
Initialize Clustering Model (K-Means)Initializes the hyperparameters of the K-Means algorithm. You can either directly set the hyperparameters or specify multiple values for each hyperparameter. If you specify multiple values for each hyperparameter, the Train Clustering Model VI uses grid search to find the optimal set of hyperparameters.
Set Clustering ModelSets properties for a trained clustering model before deployment.
Train Clustering ModelTrains a clustering model.

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