Central Limit Theorem and Machine Learning | Part-1

 By Medium - 2020-11-29

Description

Note: Here I will try to cover the idea of the Central Limit Theorem, and it’s significance in statistical analysis, and how it is useful…

Summary

  • Note: CLT will be valid when the samples are reasonably large.
  • If we have fewer data points, then the samples have to be small, which is not an ideal case to justify CLT.
  • If the whole deterministic part of Y is explained by X, then the model_error depicts only the random part and should have a normal distribution(according to CLT).So if the error distribution is normal, then we may suggest that the model is successful, and we can apply linear algorithms to the dataset for better results.

 

Topics

  1. Backend (0.34)
  2. Machine_Learning (0.29)
  3. NLP (0.17)

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