Data Warehousing and Data Mining · Unit 3 · 3 hrs
Data Preprocessing
Exam-focused notes for Data Preprocessing (Data Warehousing and Data Mining, CSC420): what the TU syllabus asks and how it has actually been tested, with 5 solved past questions from this unit.
What this unit covers
- Data cleaning
- Data integration and transformation
- Data reduction
- Data discretization and Concept Hierarchy Generation
- Data mining primitives
Data cleaning
Describe any two methods of handling noisy data. [5]
Noisy data refers to data that contains errors, outliers, or random variance that deviates from the expected values. Real world data tends to be incomplete, noisy, and inconsistent. Data cleaning attempts to smooth out noise and correct inconsistencies in t...
Full solved answer →Discuss different ways of smoothing noisy data along with suitable examples. [5]
--- Noisy data refers to data that contains errors, outliers, or random variance that can mislead data mining algorithms. Smoothing is the process of removing such noise to reveal underlying patterns. --- Binning smooths data by sorting values and partition...
Full solved answer →Data integration and transformation
Why data normalization is important in data mining? Explain min-max and Z-score normalization approach. [5]
Data normalization is important in data mining for the following reasons: - Equal weight to all attributes: Without normalization, attributes with larger ranges (e.g., income: 10,000-100,000) can dominate attributes with smaller ranges (e.g., age: 1-100), b...
Full solved answer →Data discretization and Concept Hierarchy Generation
Define data discretization. Describe the tasks for data preprocessing. [5]
--- Data discretization is a technique of data preprocessing that transforms continuous (numeric) data into discrete intervals or categories. Instead of working with raw continuous values, the data is divided into a finite number of intervals or bins, and e...
Full solved answer →Data mining primitives
Explain the primitives of data mining query language. [5]
A data mining query is used to specify a data mining task and is input to the data mining system. It is defined in terms of data mining primitives, which allow the user to interactively communicate with the data mining system in order to direct the mining p...
Full solved answer →Make Unit 3 stick
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