Define knowledge based Inductive learning.

Define knowledge based Inductive learning.
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KBIL algorithm finds inductive hypotheses that explain sets of observations with the help of background knowledge.
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Computational learning theory analyzes the sample complexity and computational complexity of a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning e) Knowledge based learning

Description : Computational learning theory analyzes the sample complexity and computational complexity of a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning e) Knowledge based learning

Last Answer : b) Inductive learning

Computational learning theory analyzes the sample complexity and computational complexity of __________ a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning

Description : Computational learning theory analyzes the sample complexity and computational complexity of __________ a) Unsupervised Learning b) Inductive learning c) Forced based learning d) Weak learning

Last Answer : b) Inductive learning

Define Inductive Learning.

Description : Define Inductive Learning.

Last Answer : An algorithm for supervised learning is given as input the correct value of the unknown function for particular inputs and it must try to recover the unknown function.

How many literals are available in top-down inductive learning methods? a) 1 b) 2 c) 3 d) 4

Description : How many literals are available in top-down inductive learning methods? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

Inductive learning involves finding a __________ a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis

Description : Inductive learning involves finding a __________ a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis

Last Answer : a) Consistent Hypothesis

Inductive learning involves finding a a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis e) Estimated Hypothesis

Description : Inductive learning involves finding a a) Consistent Hypothesis b) Inconsistent Hypothesis c) Regular Hypothesis d) Irregular Hypothesis e) Estimated Hypothesis

Last Answer : a) Consistent Hypothesis

A _________ is used to demonstrate, on a purely syntactic basis, that one formula is a logical consequence of another formula. a) Deductive Systems b) Inductive Systems c) Reasoning with Knowledge Based Systems d) Search Based Systems

Description : A _________ is used to demonstrate, on a purely syntactic basis, that one formula is a logical consequence of another formula. a) Deductive Systems b) Inductive Systems c) Reasoning with Knowledge Based Systems d) Search Based Systems

Last Answer : a) Deductive Systems

Define Inductive Logic Programming (ILP).

Description : Define Inductive Logic Programming (ILP).

Last Answer : ILP techniques perform KBIL on knowledge that is expressed in first order logic. ILP methods can learn relational knowledge that is not expressible in attribute based systems.

Which combines inductive methods with the power of first-order representations? a) Inductive programming b) Logic programming c) Inductive logic programming d) Lisp programming

Description : Which combines inductive methods with the power of first-order representations? a) Inductive programming b) Logic programming c) Inductive logic programming d) Lisp programming

Last Answer : c) Inductive logic programming

Which is the first AI programming language? a) BASIC b) FORTRAN c) IPL(Inductive logic programming) d) LISP

Description : Which is the first AI programming language? a) BASIC b) FORTRAN c) IPL(Inductive logic programming) d) LISP

Last Answer : d) LISP

Modern NLP algorithms are based on machine learning, especially statistical machine learning. a) True b) False

Description : Modern NLP algorithms are based on machine learning, especially statistical machine learning. a) True b) False

Last Answer : a) True

Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent

Description : Which agent deals with happy and unhappy states? a) Simple reflex agent b) Model based agent c) Learning agent d) Utility based agent

Last Answer : d) Utility based agent

Unsupervised learning is A. learning without computers B. problem based learning C. learning from environment D. learning from teachers

Description : Unsupervised learning is A. learning without computers B. problem based learning C. learning from environment D. learning from teachers

Last Answer : C. learning from environment

Ability to learn how to do tasks based on the data given for training or initial experience A. Self Organization B. Adaptive Learning C. Fault tolerance D. Robustness

Description : Ability to learn how to do tasks based on the data given for training or initial experience A. Self Organization B. Adaptive Learning C. Fault tolerance D. Robustness

Last Answer : B. Adaptive Learning

Classifying email as a spam, labeling webpages based on their content, voice recognition are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Description : Classifying email as a spam, labeling webpages based on their content, voice recognition are the example of _____. A. Supervised learning B. Unsupervised learning C. Machine learning D. Deep learning

Last Answer : A. Supervised learning 

Define Active Learning.

Description : Define Active Learning.

Last Answer : The agent must learn what to do. An agent must experience as much as possible of its environment in order to learn how to behave in it.

Define Passive learning.

Description : Define Passive learning.

Last Answer : The agent’s policy is fixed and the task is to learn the utilities of states, this could also involve learning a model of the environment.

Define Bayesian Learning.

Description : Define Bayesian Learning.

Last Answer : It calculates the probability of each hypotheses, given the data and makes predictions on that basis, (i.e.) predictions are made by using all the hypotheses, weighted by their probabilities rather than by using just single “best” hypotheses.

Define PAC – Learning Algorithm.

Description : Define PAC – Learning Algorithm.

Last Answer : An learning algorithm that return hypotheses that are approximately correct is called PAC learning algorithm.

Define Regression learning.

Description : Define Regression learning.

Last Answer :  Learning a continuous valued function is called regression learning.

Define Classification Learning.

Description : Define Classification Learning.

Last Answer :  Learning a discrete valued function is called is called classification learning. 

Define Reinforcement Learning

Description : Define Reinforcement Learning

Last Answer : This Learning is rather than being told what to do by teacher, a reinforcement learning agent must learn from occasional rewards. Example If taxi driver does not get a tip at the end of journey, it gives him a indication that his behaviour is undesirable.

What is Machine learning? a) The autonomous acquisition of knowledge through the use of computer programs b) The autonomous acquisition of knowledge through the use of manual programs c) The selective acquisition of knowledge through the use of computer programs d) The selective acquisition of knowledge through the use of manual programs

Description : What is Machine learning? a) The autonomous acquisition of knowledge through the use of computer programs b) The autonomous acquisition of knowledge through the use of manual programs c) The ... use of computer programs d) The selective acquisition of knowledge through the use of manual programs

Last Answer : a) The autonomous acquisition of knowledge through the use of computer programs

Generality is the measure of _____________ a) Ease with which the method can be adapted to different domains of application b) The average time required to construct the target knowledge structures from some specified initial structures c) A learning system to function with unreliable feedback and with a variety of training examples d) The overall power of the system

Description : Generality is the measure of _____________ a) Ease with which the method can be adapted to different domains of application b) The average time required to construct the target knowledge structures ... unreliable feedback and with a variety of training examples d) The overall power of the system

Last Answer : a) Ease with which the method can be adapted to different domains of application

Membership function can be thought of as a technique to solve empirical problems on the basis of A. knowledge B. examples C. learning D. experience

Description : Membership function can be thought of as a technique to solve empirical problems on the basis of A. knowledge B. examples C. learning D. experience

Last Answer : D. experience

Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Description : Shallow knowledge A . The large set of candidate solutions possible for a problem B. The information stored in a database that can be, retrieved with a single query C. Worth of the output of a machine learning program that makes it understandable for humans D . None of these

Last Answer : B. The information stored in a database that can be, retrieved with a single query

Evolutionary computation is A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. C. Decision support systems that contain an information base filled with the knowledge of an expert formulated in terms of if-then rules. D . None of these

Description : Evolutionary computation is A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution. C. ... the knowledge of an expert formulated in terms of if-then rules. D . None of these

Last Answer : B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution.

Expert systems A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution C. an information base filled with the knowledge of an expert formulated in terms of if-then rules D . None of these

Description : Expert systems A . Combining different types of method or information B. Approach to the design of learning algorithms that is structured along the lines of the theory of evolution C. an information base ... the knowledge of an expert formulated in terms of if-then rules D . None of these

Last Answer : C. an information base filled with the knowledge of an expert formulated in terms of if-then rules

What is Machine learning? A. The autonomous acquisition of knowledge through the use of computer programs B. The autonomous acquisition of knowledge through the use of manual programs C. The selective acquisition of knowledge through the use of computer programs D. The selective acquisition of knowledge through the use of manual programs

Description : What is Machine learning? A. The autonomous acquisition of knowledge through the use of computer programs B. The autonomous acquisition of knowledge through the use of manual programs C. The ... use of computer programs D. The selective acquisition of knowledge through the use of manual programs

Last Answer : A. The autonomous acquisition of knowledge through the use of computer programs 

The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Description : The characteristics of the computer system capable of thinking, reasoning and learning are known as ____________ a) machine intelligence b) human intelligence c) artificial intelligence d) virtual intelligence

Last Answer : c) artificial intelligence

. In an Unsupervised learning ____________ a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given

Description : . In an Unsupervised learning ____________ a) Specific output values are given b) Specific output values are not given c) No specific Inputs are given d) Both inputs and outputs are given

Last Answer : b) Specific output values are not given

Which of the following is also called as exploratory learning? a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Description : Which of the following is also called as exploratory learning? a) Supervised learning b) Active learning c) Unsupervised learning d) Reinforcement learning

Last Answer : c) Unsupervised learning

Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned

Description : Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned

Last Answer : d) All of the mentioned

In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Description : In which of the following learning the teacher returns reward and punishment to learner? a) Active learning b) Reinforcement learning c) Supervised learning d) Unsupervised learning

Last Answer : b) Reinforcement learning

Which of the following is an example of active learning? a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Description : Which of the following is an example of active learning? a) News Recommender system b) Dust cleaning machine c) Automated vehicle d) None of the mentioned

Last Answer : a) News Recommender system

Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Description : Automated vehicle is an example of ______ a) Supervised learning b) Unsupervised learning c) Active learning d) Reinforcement learning

Last Answer : a) Supervised learning

Which of the following does not include different learning methods? a) Memorization b) Analogy c) Deduction d) Introduction

Description : Which of the following does not include different learning methods? a) Memorization b) Analogy c) Deduction d) Introduction

Last Answer : d) Introduction

Which is used to choose among multiple consistent hypotheses? a) Razor b) Ockham razor c) Learning element d) None of the mentioned

Description : Which is used to choose among multiple consistent hypotheses? a) Razor b) Ockham razor c) Learning element d) None of the mentioned

Last Answer : b) Ockham razor

How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Description : How many types are available in machine learning? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

What is used in determining the nature of the learning problem? a) Environment b) Feedback c) Problem d) All of the mentioned

Description : What is used in determining the nature of the learning problem? a) Environment b) Feedback c) Problem d) All of the mentioned

Last Answer : b) Feedback

How many things are concerned in the design of a learning element? a) 1 b) 2 c) 3 d) 4

Description : How many things are concerned in the design of a learning element? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

Which modifies the performance element so that it makes better decision? a) Performance element b) Changing element c) Learning element d) None of the mentioned

Description : Which modifies the performance element so that it makes better decision? a) Performance element b) Changing element c) Learning element d) None of the mentioned

Last Answer : c) Learning element

What will take place as the agent observes its interactions with the world? a) Learning b) Hearing c) Perceiving d) Speech

Description : What will take place as the agent observes its interactions with the world? a) Learning b) Hearing c) Perceiving d) Speech

Last Answer : a) Learning

Which is the only way to learn about the different kinds of human faces? a) Perception b) Speech c) Learning d) Hearing

Description : Which is the only way to learn about the different kinds of human faces? a) Perception b) Speech c) Learning d) Hearing

Last Answer : c) Learning

Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned

Description : Which method is used to search better by learning? a) Best-first search b) Depth-first search c) Metalevel state space d) None of the mentioned

Last Answer : c) Metalevel state space

Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned

Description : Which is used to provide the feedback to the learning element? a) Critic b) Actuators c) Sensor d) None of the mentioned

Last Answer : a) Critic

What kind of observing environments are present in artificial intelligence? a) Partial b) Fully c) Learning d) Both Partial & Fully

Description : What kind of observing environments are present in artificial intelligence? a) Partial b) Fully c) Learning d) Both Partial & Fully

Last Answer : d) Both Partial & Fully

What can operate over the joint state space? a) Decision-making algorithm b) Learning algorithm c) Complex algorithm d) Both Decision-making & Learning algorithm

Description : What can operate over the joint state space? a) Decision-making algorithm b) Learning algorithm c) Complex algorithm d) Both Decision-making & Learning algorithm

Last Answer : d) Both Decision-making & Learning algorithm

Which element in the agent are used for selecting external actions? a) Perceive b) Performance c) Learning d) Actuator

Description : Which element in the agent are used for selecting external actions? a) Perceive b) Performance c) Learning d) Actuator

Last Answer : b) Performance

Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned

Description : Which is used to improve the agents performance? a) Perceiving b) Learning c) Observing d) None of the mentioned

Last Answer : b) Learning