This miniepisode discusses the technique called Cross Validation - a process by which one randomly divides up a dataset into numerous small partitions. Next, (typically) one is held out, and the rest are used to train some model. The hold out set can then be used to validate how good the model does at describing/predicting new data.
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
Dr. Erich G. Anderer, Chief of the Division of Neurosurgery and Surgical Director of Perioperative Services at NYU Langone Hospital–Brooklyn
09 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
Dr. Nolan Wessell, Assistant Professor and Well-being Co-Director, Department of Orthopedic Surgery, Division of Spine Surgery, University of Colorado School of Medicine
08 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast
NPR News: 12-08-2025 2AM EST
08 Dec 2025
NPR News Now
NPR News: 12-08-2025 1AM EST
08 Dec 2025
NPR News Now