VARIANCE IN MACHINE LEARNING
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Definition of Variance Variance is a statistical measure that indicates how far the data values or a machine learning model's predictions are spread out from their mean (average). It measures the amount of variability or dispersion in a dataset. In machine learning, variance refers to how much a model's predictions change when it is trained on different training datasets. A model with high variance is very sensitive to small changes in the training data and may overfit, while a model with low…
1Key Takeaways
- Definition of Variance Variance is a statistical measure that indicates how far the data values or a machine learning model's predictions are spread out from their mean (average).
- It measures the amount of variability or dispersion in a dataset.
- In machine learning, variance refers to how much a model's predictions change when it is trained on different training datasets.
- A model with high variance is very sensitive to small changes in the training data and may overfit, while a model with low….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that definition of Variance Variance is a statistical measure that indicates how far the data values or a machine learning model's predictions are spread out from their mean (average).
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