Tell me about preprocessing techniques? How can you resolve over fitting problem?

Question

Accepted Answer

Preprocessing techniques include data cleaning, normalization, encoding, and feature scaling. Overfitting can be resolved by using techniques like cross-validation, regularization, and early stopping.

Data cleaning involves removing missing values, outliers, and duplicates
Normalization scales the data to a range of 0 to 1
Encoding converts categorical variables into numerical values
Feature scaling standardizes the range of features
Cross-validation helps to evaluate the model's performance on unseen data
Regularization adds a penalty term to the loss function to prevent overfitting
Early stopping stops the training process when the model starts to overfit

Tell me about preprocessing techniques? How can you resolve over fitting problem?

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