Question 2
You are working on a machine learning project and have received a dataset containing numeric and categorical features. The dataset has some missing values and potential outliers. Given the following data cleaning steps:
- Use One-Hot Encoding for categorical variables.
- Impute missing values with feature’s mean for numeric features.
- Remove duplicates.
- Standardize numeric features using Z-score normalization.
- Identify and handle outliers using the IQR method.
Which of the following represents the MOST appropriate sequence for preparing the data for a machine learning model?