Homework
HW3: Vector Space Models
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HW3: Vector Space Models
Last updated
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Your task is to develop a sentiment analyzer train on the :
Create a file in the directory.
Define a function named sentiment_analyzer()
that takes two parameters, a list of training documents and a list of test documents for classification, and returns the predicted sentiment labels along with the respective similarity scores.
Use the -nearest neighbors algorithm for the classification. Find the optimal value of using the development set, and then hardcode this value into your function before submission.
The directory contains the following two files:
: a training set consisting of 8,544 labeled documents.
: a development set consisting of 1,101 labeled documents.
Each line is a document, which is formatted as follows:
Below are the explanations of what each label signifies:
0
: Very negative
1
: Negative
2
: Neutral
3
: Positive
4
: Very positive
Commit and push the vector_space_models.py file to your GitHub repository.
Define a function named sentiment_analyzer_extra()
that gives an improved sentiment analyzer.
Code Submission (1 point)
Program Execution (1 point)
Development Set Accuracy (4 points)
Evaluation Set Accuracy (4 points)
Concept Quiz (2 points)