What is data distribution in machine learning?
An example of an AI chatbot conversation about data distribution in machine learning.
What is data distribution in machine learning?
Data distribution in machine learning refers to how data points are spread across different values or categories. It affects model performance.
Why is understanding data distribution important?
Understanding data distribution helps in selecting the right algorithms, preprocessing data, and improving model accuracy.
Can you give examples of different types of data distributions?
Sure! Common types include normal distribution, uniform distribution, and skewed distribution. Each has unique characteristics.
How does data distribution impact model training?
Data distribution impacts model training by influencing how well the model learns patterns. Imbalanced distributions can lead to biased models.
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