Join Keith McCormick for an in-depth discussion in this video Training and test partitions, part of Machine Learning and AI Foundations: Classification Modeling.
- [Narrator] Okay, now we're gonna talk about a…critical concept and you're gonna want to master how to…do this in your software of choice.…But at a high level, the basics are very straight forward.…What you're gonna do is take the historical data,…on which you're gonna build the model, and you must divide…that data, or partition it, we say, into training data…and testing data.…What we all learn to do, initially, when we first…get accustomed to this, is that we do a 50% train…and a 50% test.…
These partitions are chosen at random.…What you'll notice, however,…when you're watching others perform this task,…is that sometimes the numbers won't be 50/50.…The general rule is straight forward, and it is this.…When your sample size starts to get small,…you increase the percentage on the train and…reduce the percentage on the test.…Because it still has to add up to 100%, so you'll often…see 70/30 or 80/20 and these are not unusual choices…for training and testing partitions.…
Okay, now, some advice that you'll occasionally get…
Note: These tutorials are focused on the theory and practical application of binary classification algorithms. No software is required to follow along with the course.
- Why do you need classification?
- Statistical algorithms versus machine learning algorithms
- Combining models using ensembles
- Classification modeling challenges
Skill Level Intermediate
SPSS Statistics Essential Trainingwith Barton Poulson4h 57m Beginner
Machine Learning and AI Foundations: Recommendationswith Adam Geitgey58m 7s Intermediate
1. The Big Picture: Defining Your Classification Strategy
2. How Do I Choose a "Winner"?
3. Algorithms on Parade
4. Common Modeling Challenges
Next steps3m 17s
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