Occam's Razor is a principle that suggests the simplest explanation or solution is usually the best. In the context of machine learning, this means that among multiple models that fit the data equally well, the one with the fewest assumptions or parameters is generally preferred. This is because simpler models are less likely to overfit the training data and are often more interpretable.
For example, if you have two models that predict house prices with similar accuracy, one that uses five features and another that uses twenty features, Occam's Razor would suggest choosing the model with five features. This is because the simpler model is less complex and easier to understand, maintain, and less likely to be overfitting.
In cloud computing, especially when using services like Tencent Cloud, this principle can be applied by choosing simpler, more efficient services that meet your needs without unnecessary complexity. For instance, if a basic machine learning service on Tencent Cloud can accomplish your task without requiring additional, more complex features, it would be the preferred choice according to Occam's Razor.