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WorksheetsIntroduction to Machine Learning
Total questions: 10
Worksheet time: 5mins
What is the primary objective of the minimax algorithm in game-playing scenarios?
Maximizing the player's score while minimizing the opponent's score
Randomly selecting moves to confuse the opponent
Minimizing computation time
Alpha-beta pruning improves the efficiency of the minimax algorithm by:
Expanding all possible game trees
Eliminating branches that cannot influence the final decision
Increasing the depth of the search
In adversarial search, the term "utility value" refers to:
The cost of executing a move
A numerical value representing the desirability of a game state
The number of players in the game
Which of the following is not a machine learning paradigm?
Supervised learning
Unsupervised learning
Rule-based programming
Version spaces in machine learning are used to:
Represent all hypotheses consistent with the training data
Store historical versions of datasets
Optimize neural network architectures
The PAC (Probably Approximately Correct) learning framework focuses on:
Guaranteeing exact correctness of hypotheses
Balancing accuracy and computational efficiency
Ignoring training data variability
Decision trees split data based on:
Random selection of features
Feature thresholds that maximize information gain
Predefined user rules
The k-means clustering algorithm groups data points by:
Minimizing the distance between points and cluster centroids
Maximizing variance within clusters
Using labeled training data
Naïve Bayes classifiers assume that features are:
Conditionally independent given the class
Highly correlated with each other
Irrelevant to the classification task
Which technique is used for multi-class classification?
Linear regression
One-vs-Rest (OvR)
K-means clustering
