Assignment 4

Modified: 2014/09/26 11:17 by admin - Uncategorized

The Task: Implement a Random Forest and an AdaBoost algorithms

In this task, you are asked to implement two ensemble algorithms: Random Forest and AdaBoost.

Your Task:
  • Implement a Random Forest and an AdaBoost algorithms.
  • Report results (accuracy of 10 fold cross validation) on the given benchmark datasets below.
  • Write a brief report to show your results.

  • Please use this MSWord template to report your results.
  • Do NOT plagiarize, plagiarism will be seriously penalized: You should be careful on writing your report. Whenever you are using words and works of others, citations should be made clear such that one can tell which part is actually yours. Details about how to identify a plagiarism can be found in "Introduction to the Guidelines for Handling Plagiarism Complaints".
  • Do NOT falsify results, data fraud will be even more seriously penalized: You should honestly record your results in the report, NEVER EVER modify the accuracy manually.


Benchmark Dataset (UC Irvine Machine Learning Repository)


Programming Language

  • Java / MATLAB
  • We provide the auxiliary codes to load the data and conduct the 10 fold cross validation so that the only work is to implement training and predicting functions.


For java

  • Download auxiliary codes.
  • You need to deal with missing data by yourself. (Double.NaN)
  • You need only to find and, then accomplish the train and predict methods of class RandomForest and AdaBoost
  • You need only to submit and


For matlab

  • Download auxiliary codes.
  • You need to deal with missing data by yourself. (NaN)
  • You need only to accomplish and submit RandomForest.m and AdaBoost.m.

You are encouraged to use your own implementation of base classifier, but


For those have not finished Ass2

We provide the implementation of decision tree in java from Xiao-Dong Wang and in matlab from Han-Jia Ye.



Pack your report and code into a zip file named with your student ID, e.g., ''.

The file format should be zip, no other format is acceptable.
NO submission after the deadline is acceptable!
NO email submission will be accepted!

Upload your file to FTP: (please use FTP software to upload, do not use Windows Explorer or IE)
username: mg_dm13
password: mg_dm13



We will evaluate your submission according to your implementation and report.

For implementation :
  • Efficiency
  • Performance
  • Code style

For report:
Technique: clearly explain all the component you used in your implementation
Language: concise, precise, and logical.

If plagiarism is identified, no scores will be given to this report.


Contact TA

Mr. Sheng-Jun Huang and Mr. Qing Da

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