This set of Data Mining Multiple Choice Questions & Answers (MCQs) focuses on “Data Preprocessing”.
1. Which of the following is not important in determining data quality?
a) Accuracy
b) Consistency
c) Completeness
d) Database
View Answer
Explanation: The data quality determines the usefulness of the data for the task in hand and determines whether the data satisfies the requirements. It is determined by factors such as accuracy, consistency and completeness.
2. Sometimes the users submit incorrect data in the compulsory fields to avoid divulging personal information. This is known as _____
a) Disguised missing data
b) Organized missing data
c) Characteristic missing data
d) Coordinated missing data
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Explanation: When a user is presented with certain fields to fill, which may be mandatory, the user may fill in wrong data in order to avoid submitting personal information, known as disguised missing data.
3. Data cleaning involves filling in missing values.
a) True
b) False
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Explanation: Data preprocessing consists of several steps. Data cleaning is one of the steps in it. Data cleaning involves steps such as cleaning of outliers, filling in missing values, smoothing noise.
4. Data integration is not a step in data preprocessing.
a) True
b) False
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Explanation: Data preprocessing is a technique which comprises of various steps. Data integration is one of the steps which involve combining data from various databases or files.
5. Which of the following is not true about data reduction?
a) Reduced data strives to gives same analytical results as the original data
b) Reduced data gives strives to give less accurate analytical results the original data
c) It involves dimensionality reduction
d) It involves numerosity reduction
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Explanation: Data reduction is a part of the data preprocessing. It aims to reduce the size of the data, yet give same results on analysis of the reduced data as the original data. it involves dimensionality reduction and numerosity reduction.
6. Which of the following is not a form of data transformation?
a) Normalization
b) Discretization
c) Concept hierarchy
d) Compression
View Answer
Explanation: Data transformation forms a part of the data preprocessing techniques. It involves techniques like normalization, data discretization and concept hierarchy generation.
Sanfoundry Global Education & Learning Series – Data Mining.
To practice all areas of Data Mining, here is complete set of Multiple Choice Questions and Answers.