Based on the five major approaches in data analysis, which of the following are incorrect?1) Dimensionality reduction: to reduce the number of attributes in a dataset to improve the accuracy of the model2) Comparison: to evaluate and compare values between two or more data points3) Hypothesis: to make assumptions about the results, and then verify whether the results are true or not4) Splitting: to trim down a process from large to small, it usually divides the problem into two partsQuestion 12Select one:a.2,3b.1,3c.2,4d.1,4
Question
Based on the five major approaches in data analysis, which of the following are incorrect?1) Dimensionality reduction: to reduce the number of attributes in a dataset to improve the accuracy of the model2) Comparison: to evaluate and compare values between two or more data points3) Hypothesis: to make assumptions about the results, and then verify whether the results are true or not4) Splitting: to trim down a process from large to small, it usually divides the problem into two partsQuestion 12Select one:a.2,3b.1,3c.2,4d.1,4
Solution
The correct answer is d. 1,4.
Explanation:
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Dimensionality reduction is used to reduce the number of attributes in a dataset, but not necessarily to improve the accuracy of the model. It is mainly used to simplify the model and reduce the computational complexity.
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Splitting is not a recognized approach in data analysis. It might be a part of data preprocessing where a dataset is split into training and testing sets, but it's not an approach to analyze data.
So, both statements 1 and 4 are incorrect.
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