AI History, Ethics, and Linear Regression Quiz
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Questions and Answers

What is the primary purpose of detecting missing values and outliers in a dataset?

  • To ensure the dataset is properly formatted for machine learning algorithms
  • To prepare the dataset for statistical analysis (correct)
  • To identify potential sources of bias in the data
  • To remove irrelevant or redundant data points
  • What is the purpose of the linear regression algorithm?

  • To identify patterns and relationships within a dataset (correct)
  • To classify data points into discrete categories
  • To reduce the dimensionality of a dataset
  • To cluster similar data points together
  • Which metric is commonly used to evaluate the performance of a regression model?

  • Root Mean Squared Error (RMSE) (correct)
  • F1-score
  • Recall
  • Precision
  • What is the primary purpose of the Perceptron algorithm?

    <p>To perform binary classification of data</p> Signup and view all the answers

    What is the purpose of a confusion matrix in the context of classification models?

    <p>To summarize the performance of a classification model by showing the number of true positives, true negatives, false positives, and false negatives</p> Signup and view all the answers

    Which evaluation metric is commonly used for binary classification tasks?

    <p>Cross-entropy</p> Signup and view all the answers

    What is the purpose of calculating linear regression on a dataset?

    <p>To analyze the relationship between variables and make predictions</p> Signup and view all the answers

    Which evaluation metric is appropriate for measuring the results obtained from logistic regression in binary classification?

    <p>Area Under the Curve (AUC)</p> Signup and view all the answers

    What is one of the key purposes of improving a regression model based on results obtained?

    <p>To enhance the accuracy and predictive power of the model</p> Signup and view all the answers

    When preparing a dataset for Machine Learning, what does detecting missing values and outliers help in achieving?

    <p>Ensuring the dataset is exploitable for machine learning</p> Signup and view all the answers

    Which aspect is essential to focus on when identifying a use case for linear regression in relation to a need?

    <p>Understanding the relationship between variables in the context of the need</p> Signup and view all the answers

    In binary classification, which performance metric focuses on the balance between precision and recall?

    <p><em>F1-score</em></p> Signup and view all the answers

    What does the Perceptron algorithm primarily aim to achieve?

    <p><em>Classification</em> of data points into two categories based on a linear decision boundary</p> Signup and view all the answers

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