Machine Learning Algorithms in Java pdf download

 

Machine Learning Algorithms in Java pdf download

Machine Learning Algorithms in Java pdf download

Machine Learning Algorithms in Java pdf download

Overview:

All the algorithms discussed in this book(Machine Learning Algorithms in Java pdf download) have been implemented and made freely available on the World Wide Web  for you to experiment with. This will allow you to learn more about how they work and what they do.

The implementations are part of a system called Weka, developed at the University of Waikato in New Zealand. “Weka” stands for the Waikato Environment for Knowledge Analysis. (Also, the weka, pronounced to rhyme with Mecca, is a flightless bird with an inquisitive nature found only on the islands of New Zealand.) The system is written in Java, an objectoriented programming language that is widely available for all major computer platforms, and Weka has been tested under Linux, Windows, and Macintosh operating systems. Java allows us to provide a uniform interface to many different learning algorithms, along with methods for pre- and postprocessing and for evaluating the result of learning schemes on any given dataset. The interface is described in this chapter. There are several different levels at which Weka can be used. First of all, it provides implementations of state-of-the-art learning algorithms that you can apply to your dataset from the command line. It also includes a variety of tools for transforming datasets, like the algorithms for discretization discussed in Chapter 7. You can preprocess a dataset, feed it into a learning scheme, and analyze the resulting classifier and its performance—all without writing any program code at all. As an example to get you started, we will explain how to transform a spreadsheet into a dataset with the right format for this process, and how to build a decision tree from it.

Machine Learning Algorithms in Java pdf download

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Machine Learning Algorithms in Java pdf download

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