What are appropriate problems for Decision tree learning? Although a variety of decision-tree learning methods have been developed with somewhat differing capabilities and requirements, decision-tree learning is generally best suited to problems with the following characteristics: Video Tutorial 1. Instances are represented by attribute-value pairs. “Instances are described by a fixed set of attributes (e.g., […]
What are decision tree and decision tree learning? Explain the representation of the decision tree with an example. Decision Trees is one of the most widely used Classification Algorithm Features of Decision Tree Learning Method for approximating discrete-valued functions (including boolean) Learned functions are represented as decision trees (or if-then-else rules) Expressive hypotheses space, including
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Perspectives and Issues in Machine Learning Following are the list of issues in machine learning: 1. What algorithms exist for learning general target functions from specific training examples? In what settings will particular algorithms converge to the desired function, given sufficient training data? Which algorithms perform best for which types of problems and representations? 2.
Consistent Hypothesis, Version Space and List then Eliminate Algorithm Consistent Hypothesis The idea: output a description of the set of all hypotheses consistent with the training examples (correctly classify training examples). Video Tutorial of Consistent Hypothesis, Version Space, and List then Eliminate Algorithm Version Space Version Space is a representation of the set of hypotheses
Means-Ends Analysis Search Technique (Algorithm) – Artificial Intelligence In this tutorial, I will how to apply Means-Ends Analysis Search Technique (Algorithm) to solve the given problem. Video Tutorial – Means-Ends Analysis Means-Ends Analysis In Artificial Intelligence, we have studied many search strategies which traverse either in forward or backward direction, but a mixture of these
Simple Linear Regression Model Solved Example in Machine Learning Regression modeling is a process of determining a relationship between one or more independent variables and one dependent or output variable. Example: 1. Predicting the height of a person given the age of the person. 2. Predicting the price of the car given the car model,
Quadratic Polynomial Regression Model Solved Example in Machine Learning Regression modeling is a process of determining a relationship between one or more independent variables and one dependent or output variable. Example: 1. Predicting the price of the car given the car model, year of manufacturing, mileage, engine capacity. 2. Predicting the height of a person
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Types of Regression Models in Machine Learning Regression modeling is a process of determining a relationship between one or more independent variables and one dependent or output variable. Examples: 1. Predicting the price of the car given the car model, year of manufacturing, mileage, engine capacity, etc. 2. Predicting the height of a person given
K-Nearest Neighbors Algorithm Solved Example in Machine Learning K-Nearest Neighbors Algorithm is an instance-based supervised machine learning algorithm. It is also known as the Lazy Learner algorithm as it delays the learning process till the arrival of a new example. In this tutorial, we will understand how to apply k nearest neighbors algorithm to classify
Implementation of AO Star Search Algorithm in python – Artificial Intelligence In this tutorial, we will understand the AO Star Search Algorithm with a solved numerical example and implementation in python. Implementation of AO Star Search Algorithm in python class Graph: def __init__(self, graph, heuristicNodeList, startNode): #instantiate graph object with graph topology, heuristic values, start
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