Data Consistency in Measurements Quiz
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Questions and Answers

What is the key difference between PCA and Factor Analysis (FA) in terms of the number of axes?

  • The number of axes in PCA is equal to the number of variables, while in FA it is limited to a few factors. (correct)
  • Both PCA and FA have the same number of axes.
  • The number of axes in FA is equal to the number of variables, while in PCA it is limited to a few factors.
  • PCA has no limit on the number of axes, while FA is limited to a few factors.
  • What is the purpose of data discretization?

  • To group numerical data into categories for analysis. (correct)
  • To confuse the analysis by making data less understandable.
  • To increase the variance in the dataset.
  • To convert categorical data into numerical data.
  • In equal width binning, how is the data sorted for grouping?

  • From smallest to largest. (correct)
  • From largest to smallest.
  • No specific sorting method.
  • Based on random selection.
  • What does equal depth binning ensure?

    <p>Equal proportions of data in each category.</p> Signup and view all the answers

    What is one common issue caused by outliers in data analysis?

    <p>Causing skewedness and affecting the distribution.</p> Signup and view all the answers

    How does equal width binning handle skewed data?

    <p>It replaces skewed data with median values.</p> Signup and view all the answers

    What is the purpose of checking if scales are similar for columns with measurements?

    <p>To ensure consistency in the units of measurement</p> Signup and view all the answers

    What is the main objective of Model Planning in the software for Data Pre-Processing?

    <p>Determine methods and workflow for model building</p> Signup and view all the answers

    What is the function of the testing set in Model Building phase?

    <p>To establish the accuracy of the model</p> Signup and view all the answers

    In geospatial datasets, why is it important to check if abbreviations of locations are consistent?

    <p>To ensure accurate geographic referencing</p> Signup and view all the answers

    What differentiates the testing set from the training set in Model Building phase?

    <p>Training set helps the algorithm learn, while testing set evaluates model accuracy</p> Signup and view all the answers

    What role does Model Building phase play in developing datasets for production?

    <p>It allows testing of the final model with live data</p> Signup and view all the answers

    What is the percentage of errors in the predictions?

    <p>8.5%</p> Signup and view all the answers

    Which attribute was identified as having the best ability to increase group homogeneity?

    <p>Income</p> Signup and view all the answers

    What percentage of rows remain after removing 37 from a total of 600?

    <p>93.83%</p> Signup and view all the answers

    What is the likelihood of an individual saying 'yes' in the group with income greater than $51,284.3?

    <p>80%</p> Signup and view all the answers

    When using 'Region' as the attribute for splitting, what percentage of rows are involved?

    <p>20.83%</p> Signup and view all the answers

    How many rows are left after considering 'Age' as an attribute?

    <p>55</p> Signup and view all the answers

    What is the main disadvantage of increasing the number of epochs to an infinite number?

    <p>Increased validation loss</p> Signup and view all the answers

    In what scenario is SVM preferred over ANN?

    <p>Nonlinearly separable data</p> Signup and view all the answers

    What transformation is needed to move from a linear to a nonlinear boundary in SVM?

    <p>Data transformation into higher dimensional space</p> Signup and view all the answers

    How do kernel methods help in SVM?

    <p>They transform data into higher dimensional spaces for easier separation</p> Signup and view all the answers

    Why are ensemble classification techniques considered better than decision trees?

    <p>They combine multiple models for improved accuracy and robustness</p> Signup and view all the answers

    How is the relationship between soloist and orchestra analogous to the relationship between decision trees and ensembles?

    <p>Ensembles generally outperform an individual decision tree</p> Signup and view all the answers

    What is the main purpose of a perceptron in classification?

    <p>To determine the class of a data point based on a separating line</p> Signup and view all the answers

    In the context of support vector machines, what do support vectors represent?

    <p>Vectors used to define the plane separating two classes</p> Signup and view all the answers

    What is a common characteristic of an invalid line in classification using a perceptron?

    <p>It passes through both red and green dots</p> Signup and view all the answers

    Why are the input values normalized before being input into the perceptron for classification?

    <p>To ensure equal dispersion of values</p> Signup and view all the answers

    What happens when a data point has a negative number output after being input into the perceptron?

    <p>It is classified as belonging to the 'No' category</p> Signup and view all the answers

    How is a perceptron line used to classify data points?

    <p>By determining which side of the line a point falls on</p> Signup and view all the answers

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