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filimdb_evaluation's Introduction

imdb_evaluation

  1. Clone this repository:
git clone https://github.com/nvanva/filimdb_evaluation.git
  1. run init.sh to prepare dataset:
./init.sh
  1. create classifier.py and write the following functions:
def train(texts, labels):
    """
    Trains classifier on the given train set represented as parallel lists of texts and corresponding labels.
    :param texts: a list of texts (str objects), one str per example
    :param labels: a list of labels, one label per example
    :return: learnt parameters, or any object you like (it will be passed to the classify function) 
    """

def classify(texts, params):
    """
    Classify texts given previously learnt parameters.
    :param texts: texts to classify
    :param params: parameters received from train function
    :return: list of labels corresponding the the given list of texts
    """
  1. place classifier.py in the same folder as evaluate.py and run evaluate.py. It will score your classifier and create file preds.tsv with predictions.
python evaluate.py
  1. Upload preds.tsv to http://compai-msu.info/c/ilimdb_sentiment/description.

  2. Upload classifier.py to http://mdl.cs.msu.ru, Assignment 1 Submission.

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