LabVIEW 2017 Analytics and Machine Learning Toolkit

National Instruments (NI), the provider of solutions that enable engineers and scientists to solve the world’s greatest engineering challenges, announced LabVIEW 2017 Analytics and Machine Learning Toolkit. This solution includes VIs for training machine learning models that discover patterns in large amounts of data. You can deploy trained machine learning models to recognize patterns in new data.


About LabVIEW 2017 Analytics and Machine Learning Toolkit. The LabVIEW Analytics and Machine Learning Toolkit integrates predictive analytics and machine learning into LabVIEW. It includes VIs for training machine learning models that discover patterns in large amounts of data through anomaly detection, classification, and clustering algorithms. These models can then be deployed to recognize the patterns in new data on Windows computers or NI Linux Real-Time targets. The toolkit works well for condition monitoring and predictive maintenance applications.

The following algorithms are included with this toolkit:

- Feature reduction: PCA, Kernel PCA, Fischer Discriminant
- Anomaly detection: GMM, One-Class SVM, PCA T2/Q, SOM-MQE
- Clustering: K-means, GMM, DBSCAN
- Classification: SVM, Neural Network, Logistic Regression

The LabVIEW Analytics and Machine Learning Toolkit uses algorithms from the IMS Center Watchdog Agent.

About National Instruments. Since 1976, National Instruments has equipped engineers and scientists with tools that accelerate productivity, innovation and discovery. NI’s graphical system design approach to engineering provides an integrated software and hardware platform that speeds the development of any system needing measurement and control. The company’s long-term vision and focus on improving society through its technology supports the success of its customers, employees, suppliers and shareholders.

Product: LabVIEW Analytics and Machine Learning Toolkit
Version: 2017 version 1.0.0
Supported Architectures: x86
Website Home Page : www.ni.com
Language: english
System Requirements: PC
Supported Operating Systems: Windows 7even SP1 / 8.x / 10 / Server 2012 R2 / Server 2008 R2 SP1
Software Prerequisites: NI LabView 2017
Size: 181.7 mb