Sampling

Prior to train the model, dataset is randomly split into a training and a test dataset. The training dataset will be used to train the model, and the purpose of the test dataset is to evaluate the performance of the final model. A number of techniques are used for sampling,
(a) Simple random sampling, there is an equal chance of selecting any tuple.
(b) Stratified sampling
(c) Progressive sampling

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