120 Questions
What is the primary objective of a supervised learning model?
To predict the output based on the input variables
What is the term for the tendency of a predictive hypothesis to deviate from the expected value?
Bias
What occurs when a model performs poorly on test data due to too much training?
Overfitting
What is the term for the choice between more complex, low-bias hypotheses and simpler, low-variance hypotheses?
Bias-variance tradeoff
What is the primary goal of model evaluation in supervised learning?
To estimate the model's performance on unseen data
What type of learning involves identifying patterns in unlabelled data?
Unsupervised learning
What is the term for the amount of change in the hypothesis due to fluctuations in the training data?
Variance
What is the primary goal of utility-based learning?
To maximize the revenue based on the user's preferences
What is the primary purpose of k-fold cross-validation in supervised learning?
To minimize the loss function
What type of model is characterized by a fixed set of parameters, independent of the number of training examples?
Parametric model
What is the goal of a learning agent in utility-based learning?
To maximize the utility function
Which model is an example of a nonparametric learning method?
Table lookup
What is the main criterion for selecting a model in supervised learning?
To minimize the loss function
What is the purpose of holding out a portion of the data as a validation set in k-fold cross-validation?
To evaluate the model's performance
What is a common problem that can occur when a model is too complex and fits the training data too well?
Overfitting
What type of learning involves finding patterns in the data without a target output variable?
Unsupervised learning
What is the primary objective of model selection in supervised learning?
To choose a good hypothesis space
What is the main issue with decision trees when dealing with new examples?
They are unstable and can change the entire tree with a single new example
What is the purpose of the validation set in model evaluation?
To choose the best candidate model
What is the error rate in the context of model evaluation?
The proportion of times that h (x) ≠ y for a sample (x, y)
What is the main difference between supervised and unsupervised learning?
Supervised learning involves training a model to predict a target variable, while unsupervised learning does not
What is the primary problem with overfitting in supervised learning?
The model is too complex and fits the noise in the training data
What is the purpose of splitting the data into training and test sets?
To evaluate the performance of a trained model on unseen data
What is the main advantage of using a validation set in addition to a training and test set?
It helps us choose the best candidate model from a set of models
What is the primary objective of a machine learning algorithm in supervised learning?
To learn a function that maps from input to output
What type of learning does not rely on explicit feedback?
Unsupervised Learning
In which type of learning is the goal to maximize a reward signal?
Utility-based Learning
What is the primary advantage of supervised learning over unsupervised learning?
Improved prediction accuracy
Which type of learning is most suitable for anomaly detection?
Unsupervised Learning
What is the primary objective of model evaluation in machine learning?
To estimate the model's performance on unseen data
Which of the following is a characteristic of overfitting?
Good performance on training data but poor performance on test data
What is the primary cause of underfitting in machine learning?
Model complexity is too low
What type of separator does an SVM construct?
Maximum margin separator
Which of the following is a non-parametric method?
Support Vector Machines
What is the goal of SVMs in terms of loss?
Minimize expected generalization loss
What is the purpose of data augmentation in machine learning?
To help when data are limited
What is the main benefit of the kernel trick in SVMs?
It allows for non-linear separability
What is the purpose of a ROC curve in machine learning?
To visualize model performance
What is nonstationarity in machine learning?
The world changes over time
What is the main goal of model evaluation in machine learning?
To understand why the model made a particular prediction
What is the primary role of prior knowledge in Explanation-Based Learning?
To reduce the complexity of learning
What is the outcome of the generalized proof tree in Explanation-Based Learning?
A new rule is constructed with the parametrized goal
In Explanation-Based Learning, what is the purpose of dropping conditions from the left-hand side of the new rule?
To eliminate conditions that are true regardless of the goal
What is the primary objective of Inductive Logic Programming (ILP) techniques?
To perform knowledge-based inductive learning
What is the significance of the extension of background knowledge in Explanation-Based Learning?
It is based on extracting rules from individual observations
What is the relationship between Explanation-Based Learning and Inductive Logic Programming (ILP)?
ILP is used to perform Explanation-Based Learning
What is the key characteristic of relevance-based learning?
It uses prior knowledge in the form of determinations
What is the primary function of the background knowledge in knowledge-based inductive learning?
To help the agent infer a new, general rule that explains the observations
What type of learning is characterized by the agent using deductive form of learning and needing initial knowledge?
Knowledge-based inductive learning
What is the role of the goal predicate in relevance-based learning?
To determine the relevance of a set of features
What is the primary difference between knowledge-based inductive learning and other types of learning?
It uses prior knowledge
What is the primary function of the agent in knowledge-based inductive learning?
To use deductive form of learning with initial knowledge
What does a determination P ≻ Q imply?
If any examples match on hypothesis P, then they must also match on hypothesis Q
What is the primary function of first-order literals in Inductive Logic Programming?
To represent the examples as facts in the programs
What is the purpose of the initial hypothesis in Inductive Logic Programming?
To represent the most general rule for solving the problem
What type of literals can be added to a clause in Inductive Logic Programming?
Literals build using existing predicates, with at least one variable
What is the function of the logical inference behind the program interpreter in Inductive Logic Programming?
To derive conclusions as rules to solve the problem
What is the primary goal of Inductive Logic Programming?
To learn from examples and generalize to new situations
What is the logical relationship between hypotheses h1 and h2 if h1 is a generalization of h2?
∀ x C2(x) ⇒ C1(x)
What type of learning does a machine learning agent engage in if it maintains a single hypothesis and adjusts it as new examples arrive?
Learning by searching for the current-best-hypothesis
What is the result of a false negative example on a hypothesis?
The hypothesis is generalized to include the example
What is the version space of a hypothesis?
The set of all possible hypotheses that are consistent with the data
What is the primary goal of least-commitment search in machine learning?
To find the most specific hypothesis that is consistent with the data
What is the effect of a false positive example on a hypothesis?
The hypothesis is specialized to exclude the example
What must the boundary-set possess in order to represent the version space without the need to explore it entirely?
Two properties: every consistent hypothesis is more specific than some member of the G-set and more general than some member of the S-set
What is the primary goal of a machine learning agent in the modern approach to AI?
To design agents that already know something about the solution and are trying to learn more during the process of solving problems
What type of search is used to explore the version space in a least-commitment strategy?
Least-commitment search
What is a potential consequence of a hypothesis being more specific than some member of the G-set and more general than some member of the S-set?
It may be a consistent hypothesis, but it is not guaranteed
What is the primary goal of Explanation-Based Learning (EBL)?
To extract general rules from single examples
What is a potential consequence of a hypothesis being more general than some member of the S-set and more specific than some member of the G-set?
It is guaranteed to be a consistent hypothesis
What is the primary goal of CHOOSE-LITERAL in inductive learning?
To eliminate irrelevant hypotheses based on information gain
What is the result of resolving two clauses C1 and C2 in inverse resolution?
A new clause C that is the result of resolving C1 and C2
What is the primary advantage of using literals in inductive learning?
They can be used to represent complex relationships between variables
What is the primary objective of inductive learning with inverse deduction?
To generate new hypotheses using inverse resolution
What is the role of Ockham's razor in CHOOSE-LITERAL?
To eliminate irrelevant hypotheses based on information gain
What is the primary advantage of using inverse resolution in inductive learning?
It can be used to generate new hypotheses
What is the relationship between literals and clauses in inductive learning?
Literals are used to represent complex relationships between variables
What is the primary objective of using information gain in CHOOSE-LITERAL?
To eliminate irrelevant hypotheses
What is the result of resolving a clause C with a clause C1 in inverse resolution?
A new clause C2 that is the result of resolving C and C1
What is the primary advantage of using inductive learning with inverse deduction?
It can be used to generate new hypotheses
In a sequential environment, what is a characteristic of an agent's actions?
They have long-term consequences.
What type of environment does not change while the agent is deliberating?
Static environment
What type of agent selects actions based solely on the current percept and predefined rules or mappings from percepts to actions?
Simple reflex agent
What type of agent maintains an internal model of the world and uses it to plan and reason about actions?
Model-based reflex agent
What is a characteristic of goal-based agents?
They have explicit goals or objectives.
In a dynamic environment, what happens while the agent is acting?
The environment changes.
What is a way to classify agents based on their design and behavior?
By their design and behavior
What is a characteristic of agents in a sequential environment?
Their actions have long-term consequences.
What is the primary criteria for an agent to be successful in a fully observable environment?
The agent's performance measure is optimized.
What is the primary difference between an episodic environment and a sequential environment?
The impact of the agent's actions on the environment.
What is the primary function of sensors in an AI agent?
To perceive or gather information about the environment.
What is the primary characteristic of a deterministic environment?
The next state of the environment is completely determined by the current state and the actions taken by the agent.
What is the primary purpose of defining the environment in an AI agent?
To describe the context in which the agent operates.
What is the primary difference between a partially observable environment and a fully observable environment?
The amount of information available to the agent's sensors.
What is the primary role of actuators in an AI agent?
To take actions to manipulate the environment.
What is the primary benefit of categorizing environments into different types?
To design specific AI agents for each type of environment.
What is a potential consequence of overdependence on AI in the workforce?
A decline in certain human skills, particularly those related to problem-solving
What is a possible way to limit the impact of AI on human skills and workforce?
Developing policies that support workforce transition through retraining programs
What is the primary goal of regulating the use of AI in sensitive areas such as media and political campaigns?
To prevent the manipulation of public opinions and elections
What is the term for the ability of an agent to select actions that maximize its expected performance measure?
Rationality
What is the primary function of sensors in an AI agent?
To perceive the environment
What is the primary goal of an agent in an AI system?
To select actions that maximize its expected performance measure
What is the term for the external factors that can affect an AI agent's performance?
Environment
What is a potential consequence of AI-generated deepfakes or algorithmically curated content?
A manipulation of social and political scenarios
What is a significant concern regarding AI systems, which can lead to unfair treatment of certain groups?
Bias and discrimination
What is a potential consequence of AI technologies, in terms of personal data?
Intrusion on individuals' privacy
What is a characteristic of AI systems that enables them to adapt to new situations?
Learning from data
What is a type of AI approach that involves programming computers to manipulate symbols based on predefined rules?
Symbolic AI
What is a potential consequence of AI systems, in terms of human skills?
Erosion of human skills
What is a goal of AI systems, in terms of decision making?
To make decisions based on patterns and predictions
What is a characteristic of deep learning, a subset of machine learning?
Use of artificial neural networks with many layers
What is a potential consequence of AI systems, in terms of social manipulation?
Social manipulation and control
What is a primary concern regarding the lack of accountability in AI systems?
Determining liability for harm caused by AI systems
What is a potential consequence of over-reliance on AI in various sectors?
Dehumanization in customer service and caregiving
What is a key approach to limiting the impact of AI on job displacement?
Upskilling and reskilling workers to work alongside AI systems
What is a legal challenge arising from AI systems operating across borders?
Navigating varying international regulations
What is a potential consequence of dehumanization in various sectors?
Erosion of human skills and empathy
What is a key approach to limiting the impact of AI on social problems?
Implementing rigorous ethical guidelines for AI systems
What is a potential consequence of AI-generated content?
Intellectual property issues in AI-generated content
What is a key challenge in assigning liability for harm caused by AI systems?
Clarifying the responsibility of AI system developers and users
Learn about the basics of machine learning, including hypothesis, model, and function approximation. Understand how to evaluate the quality of a hypothesis and its performance on unseen data.
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