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General Tech Learning Aids/Tools 2 years ago
Posted on 16 Aug 2022, this text provides information on Learning Aids/Tools related to General Tech. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.
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This is a very fundamental question but I want to make sure I get this right.
K-fold cross validation will only help in predicting the accuracy and other metrics of the model but not really improve the model. Is that correct?
I am trying to read and learn about it and what I find is this is the approach mainly to have a better estimate of the model performance than applying it on single data set. However, CV cannot directly help in model improvement as in it will not give out a better model. You would have to tune the model again through different algorithms and again run it through CV to compare performance.
Is my understanding correct?
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