Machine Learning

ID3 Algorithm Decision Tree – Solved Example

Download Final Year Projects   Join for Regular Updates ID3 Algorithm Decision Tree – Solved Example – Machine Learning Problem Definition: Build a decision tree using ID3 algorithm for the given training data in the table (Buy Computer data), and predict the class of the following new example: age<=30, income=medium, student=yes, credit-rating=fair age income student […]

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What is Machine Learning? Components and Applications

Download Final Year Projects   What is Machine Learning? Components and Applications of Machine Learning Definition of Machine Learning: Learning is any process by which a system improves performance from experience. A branch of artificial intelligence, concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data. Definition

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Principal Component Analysis Solved Example

Download Final Year Projects   Principal Component Analysis Solved Example Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. In this article, I will discuss how to find the

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Principal component analysis in Machine Learning

Download Final Year Projects   Introduction to Principal component analysis in Machine Learning Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. The number of principal components is less

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Dimensionality reduction in Machine Learning

Download Final Year Projects   The complexity of any classification or regression algorithm depends on the number of inputs to the model. This determines the time and space complexity and the necessary number of training examples to train such a classification or regression algorithm. In this article, we discuss what is dimensionality reduction, how dimensionality

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Appropriate Problems For Decision Tree Learning

Download Final Year Projects   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

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Decision Tree Representation in Machine Learning

Download Final Year Projects   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

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