Vidyashri M H

Lex Program to count numbers of lines, words, spaces and characters

Lex Program to count the numbers of lines, words, spaces, and characters in a given statement Problem definition: Write a lex program to recognize lines, words, spaces, and characters in a given statement and display the numbers of lines, words, spaces, and characters on standard output. Structure of LEX Program: %{Definition section%} %% Rules section

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Lex Program to recognize comments, numbers, identifiers, and strings

Lex Program to recognize and display comments, numbers, identifiers, and strings in a given statement Problem definition: Write a lex program to recognize comments, numbers, identifiers, and strings in a given statement and display them on standard output. Structure of LEX Program: %{Definition section%} %% Rules section %% User Subroutine section   Click here to

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Principal Component Analysis Solved Example

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 principal components with a simple

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Principal component analysis in Machine Learning

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 than or equal to the

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Dimensionality reduction in Machine Learning

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 reduction is implemented, and the

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