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Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question. You have a dataset that contains a column named Column1. Some of the values in Column1 are empty. You need to replace the empty values by using probabilistic Principal Component Analysis (PCA). The solution must use a native module. Which module should you use?
Correct Answer: E
Explanation/Reference: Explanation: You can use the Clean Missing Data module in Azure Machine Learning Studio, to remove, replace, or infer missing values. This module supports multiple type of operations for "cleaning" missing values, including: Replacing missing values with a placeholder, mean, or other value Completely removing rows and columns that have missing values Inferring values based on statistical methods You can choose to replace using Probabilistic PCA: Replaces the missing values by using a linear model that analyzes the correlations between the columns and estimates a low-dimensional approximation of the data, from which the full data is reconstructed. References: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean- missing-data
