Classification Techniques in AI
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Questions and Answers

What is the purpose of an ordered rule set?

  • To assign a test record to a class label based on the highest ranked rule triggered (correct)
  • To rank rules based on their quality
  • To evaluate the performance of a classification model
  • To extract rules directly from data

    • What is the name given to an ordered rule set?

  • Decision tree
  • Decision list (correct)
  • Sequential covering
  • Rule-based classification

    • What is the default class assigned to a test record if none of the rules are triggered?

  • Unknown class
  • Random class
  • Majority class (correct)
  • Minority class

    • What is the main difference between rule-based ordering and class-based ordering?

    <p>Rule-based ordering ranks rules by quality, while class-based ordering ranks rules by class</p> Signup and view all the answers

    What is the name of the algorithm based on Rule-Based Classification used for learning a disjunctive set of rules?

    <p>Sequential Covering</p> Signup and view all the answers

    What is the purpose of the Learn-One-Rule function in the Sequential Covering algorithm?

    <p>To grow a rule</p> Signup and view all the answers

    What is the main advantage of the Direct Method in building classification rules?

    <p>It extracts rules directly from data</p> Signup and view all the answers

    What is the purpose of the Indirect Method in building classification rules?

    <p>To extract rules from other classification models</p> Signup and view all the answers

    What is the main objective of using Bayes theorem in classification?

    <p>To maximize the posterior probability of the class labels</p> Signup and view all the answers

    What is the formula to calculate the posterior probability in Bayes theorem?

    <p>P(Y | X) = P(X | Y) * P(Y) / P(X)</p> Signup and view all the answers

    What is the goal of Naïve Bayes classification?

    <p>To predict the class label that maximizes the posterior probability</p> Signup and view all the answers

    What is the advantage of using ensemble classifiers?

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

    What is the purpose of evaluating the performance of a classification model?

    <p>To compare the performance of different classification models</p> Signup and view all the answers

    What is the formula to calculate the precision of a classification model?

    <p>Precision = TP / (TP + FP)</p> Signup and view all the answers

    What is the purpose of using the F-measure in classification evaluation?

    <p>To balance the precision and recall of the classification model</p> Signup and view all the answers

    What is the purpose of using Rule-based classification?

    <p>To increase the interpretability of the classification model</p> Signup and view all the answers

    What is the purpose of using Bayes theorem in Naïve Bayes classification?

    <p>To compute the posterior probability of the class labels</p> Signup and view all the answers

    What is the advantage of using Bayes theorem in classification?

    <p>To provide a probabilistic framework for classification</p> Signup and view all the answers

    What is a characteristic of Naïve Bayes classifiers?

    <p>Robust to isolated noise points</p> Signup and view all the answers

    What is the purpose of a rule in a Rule-Based Classifier?

    <p>To classify records by using a collection of “if…then…” rules</p> Signup and view all the answers

    What happens when a rule in a Rule-Based Classifier covers a record?

    <p>The rule is fired or triggered</p> Signup and view all the answers

    What is a limitation of Naïve Bayes classifiers?

    <p>They are sensitive to irrelevant attributes</p> Signup and view all the answers

    What can be used as an alternative to Naïve Bayes classifiers when dealing with correlated attributes?

    <p>Bayesian Belief Networks (BBN)</p> Signup and view all the answers

    What is the structure of a rule in a Rule-Based Classifier?

    <p>Condition → y, where y is a class label</p> Signup and view all the answers

    Study Notes

    Classification Techniques

    • Base Classifiers:
      • Decision Tree based Methods
      • Naïve Bayes
      • Rule-based Methods
      • Bayesian Belief Networks
      • Nearest-neighbor
      • Support Vector Machines
      • Neural Networks, Deep Neural Nets
    • Ensemble Classifiers:
      • Boosting
      • Bagging
      • Random Forests

    Bayes Classifier

    • A probabilistic framework for solving classification problems
    • Conditional Probability: P(Y|X) = P(X,Y) / P(X)
    • Bayes theorem: P(Y|X) = P(X|Y) * P(Y) / P(X)

    Using Bayes Theorem for Classification

    • Consider each attribute and class label as random variables
    • Goal is to predict class Y given attributes X1, X2, …, Xd
    • Want to find the value of Y that maximizes P(Y| X1, X2, …, Xd)

    Naïve Bayes

    • Robust to isolated noise points
    • Handle missing values by ignoring the instance during probability estimate calculations
    • Robust to irrelevant attributes
    • Redundant and correlated attributes will violate class conditional assumption

    Rule-Based Classifier

    • Classify records by using a collection of “if…then…” rules
    • Rule format: r: (Condition) → y, where Condition is a conjunction of attributes and y is the class label
    • A rule covers a record if the precondition of the rule matches the attributes of the record

    Rule-Based Classifier (cont.)

    • Rule-based Classifier can be Unordered or Ordered
    • In Ordered Rule Set, rules are rank ordered according to their priority (accuracy, coverage, total description length, or the order in which the rules are generated)

    Building Classification Rules

    • Direct Method: Extract rules directly from data (e.g. RIPPER, CN2, Holte’s 1R)
    • Indirect Method: Extract rules from other classification models (e.g. decision trees, neural networks)

    Direct Method: Sequential Covering

    • A popular algorithm based on Rule-Based Classification used for learning a disjunctive set of rules
    • Main steps:
      • Start from an empty rule
      • Grow a rule using the Learn-One-Rule function
      • Remove training records covered by the rule

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    Quiz Team

    Description

    This quiz covers basic concepts and techniques of classification, including Naïve Bayes, Rule-Based, and evaluation methods. It also touches on base classifiers like Decision Trees, Bayesian Belief Networks, and Support Vector Machines.

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