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Consider a dataset with various attributes such as numerical, categorical, and text data. Using the AutoML data exploration notebook, identify the key attributes that should be analyzed to gain a comprehensive understanding of the dataset. Discuss how these attributes influence the model selection and preprocessing steps in AutoML.
A
Data type, missing values, outliers, and feature importance.
B
Data distribution, correlation matrix, dimensionality, and class imbalance.
C
Data volume, data quality, feature relevance, and data consistency.
D
Data schema, data lineage, data transformation, and data integration.