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Imputation involves replacing missing values with statistically derived estimates such as mean, median, mode, or values predicted by machine learning models. This approach ensures the dataset remains robust without significant loss of information. For example, imputing the mean for missing sales figures can maintain the overall trend without introducing bias. Advanced imputation techniques, such as regression or k-nearest neighbors, provide more accurate estimations based on the relationships within the data. Proper handling of missing data is crucial to preserve dataset integrity and improve the reliability of subsequent analyses. Why Other Options Are Incorrect: • A: Discarding the entire dataset is impractical and results in data loss. • B: Using random values introduces noise and reduces reliability. • D: Ignoring missing data can lead to biased or incomplete analysis. • E: Replacing with zeros distorts the dataset, particularly in numerical or continuous data.
World Vegetable Centre previously known as Asian Vegetable Research and Development Centre is located at
Which of the following is not a rule made under National Food Security Act, 2013?
Pradhan Mantri Krishi Sinchai Yojana (PMKSY) has been formulated with the vision of ____
Loose smut of wheat is caused by
Which of the following is land holding of marginal farmers?
Gughia weevil is a pest of:
Netting is a common practice recommended for:
ICAR- Indian Institute of Rice Research is situated at
Which part of the insect's body is often fused with the head to form the cephalothorax?
Which river basin cover the largest surface water irrigation in India?