/ID3

This is the ID3 implementation project for the course Artificial Intelligence at AUEB for the year 2021-2022.

Primary LanguageJavaGNU General Public License v3.0GPL-3.0

ID3 Algorithm

implemented in Java

EVANGELOS PIPILIKAS

File compilation

  1. Open the command line
  2. Change the directory to the one that contains the project
  3. Run the command: javac ID3.java

Running the algorithm

>!< Please pay attention to the order that parameters should be given. >!<
  • To execute the algorithm, make sure you have put the train and data files at the same folder with algorithm ( or make sure you put the right directory).
  • The algorithm will expect the above parameters with the exact same order that are described:
    • featureFileName: the file name that contains the vocabulary (.vocab file)
    • trainDataFileName: the file name of the training examples (.feat file)
    • testDataFileName: the file name of the test examples (.feat file)
    • pruningParameter: the parameter we use to prune the tree (double and should be between 0.0 and 1.0, we recommend > 0.80 and <0.97)
    • nParameter: the first n most common words
  • Here is an example of input: java ID3 imdb.vocab trainlabeledBow.feat testlabeledBow.feat 0.90 100
>!< In case there is an OutOfMemoryError, please use less words in the .vocab file. >!<

Source of data in test_examples folder: https://ai.stanford.edu/~amaas/data/sentiment/