What are some disadvantages of batch learning algorithms?Select one:a.They require a large amount of resourcesb.They are slow to adapt to changes in the datac.They require a small amount of datad.They are prone to overfitting
Question
What are some disadvantages of batch learning algorithms?Select one:a.They require a large amount of resourcesb.They are slow to adapt to changes in the datac.They require a small amount of datad.They are prone to overfitting
Solution
The disadvantages of batch learning algorithms are:
a. They require a large amount of resources: Batch learning algorithms often require a lot of computational resources because they need to process all the data at once. This can be a problem if you have a large dataset or limited computational resources.
b. They are slow to adapt to changes in the data: Since batch learning algorithms process all the data at once, they can be slow to adapt to changes in the data. This means that if new data comes in that is different from the data the algorithm was trained on, the algorithm may not perform well.
d. They are prone to overfitting: Overfitting is a common problem in machine learning where a model performs well on the training data but poorly on new, unseen data. Batch learning algorithms are particularly prone to overfitting because they
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