Classification VIs

LabVIEW 2018 Analytics and Machine Learning Toolkit Help

Edition Date: July 2018

Part Number: 377059B-01

»View Product Info
Download Help (Windows Only)

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 Classification VIs to initialize, train, evaluate, and deploy classification models that classify given sets of categories.

Palette ObjectDescription
Deploy Classification ModelDeploys a trained classification model and returns predicted labels of input data.
Evaluate Classification ModelEvaluates a trained classification model by using new test data with labels.
Initialize Classification Model (LR)Initializes the hyperparameters of the logistic regression (LR) algorithm. You can either set the hyperparameters or specify multiple values for each hyperparameter. If you specify multiple values for each hyperparameter, the Train Classification Model VI uses grid search to find the optimal set of hyperparameters.
Initialize Classification Model (NN)Initializes the hyperparameters of the neural network (NN) 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 Classification Model VI uses grid search to find the optimal set of hyperparameters. This VI supports single hidden layers only.
Initialize Classification Model (SVM)Initializes the hyperparameters of the support vector machine (SVM) 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 Classification Model VI uses grid search to find the optimal set of hyperparameters.
Set Classification ModelSets properties for a trained classification model before deployment.
Train Classification ModelTrains a classification model.

WAS THIS ARTICLE HELPFUL?

Not Helpful