dataset before applying a data mining technique. a data quality task; it aims to solve many...

 

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dataset before applying a data mining technique. a data quality task; it aims to solve many problems that may exist in a 1. Give three data cleansing tasks: 10.5 Mark 3-15 Marks 2. Give three data integration issues. 10.5 Mark 3 1.5 Marks] 3. Explain the difference between dimensionality reduction and sampling. [1 Mark 2 =2 Marks] Consider the data set in Table 1 to answer. In case of stratified sampling, if we select two samples from A, what would be the number of samples taken from each of B, C and D, and the size of the sample? Answer here. (1 mark] Table 1. A D B B C C B A A B B A dataset before applying a data mining technique. a data quality task; it aims to solve many problems that may exist in a 1. Give three data cleansing tasks: 10.5 Mark 3-15 Marks 2. Give three data integration issues. 10.5 Mark 3 1.5 Marks] 3. Explain the difference between dimensionality reduction and sampling. [1 Mark 2 =2 Marks] Consider the data set in Table 1 to answer. In case of stratified sampling, if we select two samples from A, what would be the number of samples taken from each of B, C and D, and the size of the sample? Answer here. (1 mark] Table 1. A D B B C C B A A B B A

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Chapter 3 Data Preprocessing 1 Data Cleansing Tasks 105 Marks Data cleansing tasks are crucial for ensuring the quality of a dataset before applying d... View the full answer