Exam questions collection

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Machine Learning ( book | pdf ) 5. Data mining (77 | 89) 5.2. Representation of input data ➢ Which of the following statements is correct? • Numerical attributes include counts and continuous attributes. • The categorical attributes include the counts, nominal attributes, ordinal attributes. • The categorical attributes include discrete attributes, nominal and ordinal. • The numerical attributes include the counts, attributes continuous and discrete attributes. • Numerical attributes can be discrete or continuous 5.4. Analysis methodologies ➢ With reference to the data mining analysis, which of the following statements is correct • In supervised learning analysis, there is a target variable which can be either categorical or continuous. [90 | 102] • In Classification the target variable is categorical. [92 | 104] 6. Data preparation (95 | 107) 6.2. Data Transformation ➢ Data standardization aims to: • Return the attribute values within a predefined range. [99 | 111] • Transforming the attribute values so the range of attribute values is the same 6.3. Data Reduction ➢ With reference to the methods of filter for the selection of the attributes, which of the statements are correct? • Select the relevant attributes, iteratively using the learning algorithm used to predict the value of the target variable. • They create new variables since the existing attributes. • They create new attributes since the existing attributes. • They select the relevant attributes in the process of the learning model generation. • Select the relevant attributes during the generation process of the learning model. • No answer is right. [102 | 114] ➢ With reference to the analysis of the principal component analysis (PCA), which statements are correct? [105 | 117] • Vectors represent the main…