lab3: Language Classifier

Usage

Place your desired training and testing data files into lab3/input folder. After training the Classifier, it will generate object file with the given output file name in lab3/output directory.

• python lab3.py train <examples> <hypothesisOut> <learning-type> to read the labeled examples and perform training ("ada" or "dt").
  • examples is a file containing labeled examples.
  • hypothesisOut specifies the file name to write your model to.
  • learning-type specifies the type of learning algorithm you want to run, it is either "dt" or "ada".
    • You can edit the desired DEPTH and ENSEMBLE_SIZE in lab3.py file.
• python lab3.py predict <hypothesis> <file> to classify each line as either English or Dutch using the specified hypothesis.
  • hypothesis is a trained decision tree or ensemble created by the classifier
    • It will be in lab3/output directory. Simply put the name of the file and it will read it from directory
  • file is a file containing lines of 15 word sentence fragments in either English or Dutch.

Example Usage

Remember to place the testing and training data files into lab3/input directory.

Train an AdaBoost model:

• python lab3.py train main_train.dat ensemble.oj ada

Let AdaBoost model predict the classifications of sentences in test data file:

• python lab3.py predict ensemble.oj main_test.dat

Train a Decision Tree model:

• python lab3.py train main_train.dat tree.oj dt

Let Decision Tree model predict the classifications of sentences in test data file:

• python lab3.py predict tree.oj main_test.dat