Given a string s of lowercase alphabets and a number k, the task is to print the minimum value of the string after removal of k characters. The value of a s ...

A. Introduction to neural networksB. ANN architectures Feedforward networks Feedback networks Lateral networks C. Learning methods Supervised learning Unsup ...

When a contiguous block of text is selected in a PDF viewer, the selection is highlighted with a blue rectangle. In this PDF viewer, each word is highlighte ...

The Utopian Tree goes through 2 cycles of growth every year. Each spring, it doubles in height. Each summer, its height increases by&nbs ...

Introduction Storing data in local computer memory represents the fastest and most reliable means to access it. The data could reside anywhere. However, you ...

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Unstructured data files consist of a series of bits. The file doesn’t separate the bits from each other in any way. You can’t simply look into the file and ...

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Introduction Boosting (originally called hypothesis boosting) refers to any Ensemble method that can combine several weak learners into a strong learner. Th ...

Another very popular Boosting algorithm is Gradient Boosting. Just like AdaBoost,Gradient Boosting works by sequentially adding predictors to an ensemble,

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The last Ensemble method we will discuss in this series is called stacking (short for stacked generalization). It is based on a simple idea: instead of usin ...

Introduction Many Machine Learning problems involve thousands or even millions of features for each training instance. Not only does this make training extr ...

Databases come in all sorts of forms. For example, AskSam (http://asksam.en.softonic.com/) is a kind of free-form textual database. However,

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Before we dive into specific dimensionality reduction algorithms, let’s take a look at the two main approaches to reducing dimensionality: projection and Manifold Learning. Projection In most real-…