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This learning application features a training set, test set and a tree builder. Each example in the datasets can be viewed, moved to or out of the training and test sets. The tree builder and the tree itself are also easily manipulated. After viewing the tree, the testing can begin, with the results being displayed in the test set.
For more information about this applet please refer to the main page for more information:

Learn! Decision Trees with Apriori is a tutorial applet demonstrating how to use a decision tree for real-world applications.
The applet features:
(1) A tutorial – which takes the student through the fundamental concepts of decision trees.
(2) Example datasets and a complete implementation for teaching and illustrating decision trees.
(3) A gallery of 12 advanced tutorials with implementation details and source code.
(4) A Problem Solver, which can be used to identify the appropriate number of decision tree leaves, and the appropriate classification criteria for training examples, for a given problem.
(5) Support for sorting and searching datasets on the basis of their column or feature values.
(6) Test data sets, which can be used to evaluate the performance of a trained decision tree.
(7) Algorithms and heuristics for building decision trees.
(8) An example implementation of the C4.5 algorithm for building decision trees.
(9) A discussion forum, where problems and questions can be posted and answered.
(10) A command line interface for the applet which can be used to create test data sets for a given problem.

This is the sequel to the Learn! Decision Trees tutorial applet. In it, the student learns how to implement a bootstrap aggregation decision tree. The applet features:
(1) A tutorial – which takes the student through the fundamental concepts of bootstrap aggregation decision trees.
(2) Example datasets and a complete implementation for teaching and illustrating decision trees.
(3) A gallery of 12 advanced tutorials with implementation details and source code.
(4) A Problem Solver, which can be used to identify the appropriate number of decision tree leaves, and the appropriate classification criteria for training examples, for a given problem.
(5) Support for sorting and searching datasets on the basis of their column or feature values.
(6) Algorithms and heuristics eea19f52d2

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Download YouTube videos easily and free. Support mp3, mp4, 3gp, avi, mkv formats. Software also works as YouTube converter and YouTube downloader which allows you to download as mp3.

Video Convert Factory Free is a very powerful video converter software for converting the most popular video formats. It offers a lot of options to help you convert videos with ease, such as batch conversion, video editor, DVD ripping, video to DVD, video downloader and so on.

Video Convert Factory Free includes the following features:

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Video editor:

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