Description: Adaptive boosting(AdaBoost) algorithms are used by many other machine learning algorithms to improve their performance. Algorithm combines several weak hypothesis to create stronger hypothesis among them. I have implemented java program for binary and real adaptive boosting algorithms. You can know more about adaptive boosting at:http://en.wikipedia.org/wiki/AdaBoost#Overview
How do I, as a developer, start working on the project?
- What dependencies does it have (where are they expressed) and how do I install them? A. _It doesn't have any dependencies.
- How can I see the project working before I change anything? A. _Just run run the code in Eclipse.
- Required Eclipse with jdk 1.6 or higher
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Input is text file. Sample dataset is attached in project
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First element of first line is number of iterations for program
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Second element of first line is number of elements.
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Third element of first line is Ebsilon value
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_Second, Third and fourth lines are element names,associated values and probability of each elements. _
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Output is boosted hypothesis.
- Email : parthtrivedi2492@gmail.com
- "Please open github issues, emails can get messy"
MIT License