Cross-Validation

In this video, we take a look at estimating the accuracy of machine learning models. We use different sampling methods and the Test & Score widget to determine average accuracy over multiple tries. We also introduce the concept of cross-validation for accuracy estimation.
This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of interactive data analysis using Orange Data Mining software (https://orangedatamining.com).
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The development of this video series was supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenia Ministry of Digital Transformation, European Union (including xAIM and ARISA) and Google.org/Tides foundation.

#machinelearning #orange #visualanalytics #datamining
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Written by: Blaž Zupan (http://biolab.si/blaz)
Presented by: Noah Novšak
Production and edit: Lara Zupan
Intro/outro: Agnieszka Rovšnik
Music by: Damjan Jović – Dravlje Rec
Orange is developed by Biolab at University of Ljubljana (https://www.biolab.si)