Calculate accuracy score

[jo-elimu]

Accuracy score 0.75

Which issue does this PR address?

Resolves #20

Summary by CodeRabbit

• New Features
  • Introduced an accuracy score metric for model evaluation, now recorded in a dedicated file.
  • Enhanced validation script to calculate and output the accuracy score alongside existing metrics.
• Improvements
  • Updated print statements for better readability and performance in the validation script.

[coderabbitai]

Walkthrough

The changes introduce a new file to record the accuracy score of a predictive model and enhance the functionality of the validation script. The validation script now calculates and outputs the accuracy score alongside existing metrics, improving the clarity of output messages and the overall evaluation of model performance.

Changes

Files	Change Summary
pmml/step3_predict/step3_2_accuracy_score.txt	Added a file that contains the accuracy score of 0.75.
pmml/step3_predict/step3_2_validate.py	Improved print statements using f-strings, added accuracy score calculation, and output to a text file.

Assessment against linked issues

Objective	Addressed	Explanation
Add accuracy score (#20)	✅

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Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 4ac0027 and ae3109c.

Files selected for processing (2)

• pmml/step3_predict/step3_2_accuracy_score.txt (1 hunks)
• pmml/step3_predict/step3_2_validate.py (2 hunks)

Files skipped from review due to trivial changes (1)

• pmml/step3_predict/step3_2_accuracy_score.txt

Additional comments not posted (10)

pmml/step3_predict/step3_2_validate.py (10)

5-5: LGTM!

The import of accuracy_score from sklearn.metrics is relevant to the PR objective and is correctly placed at the top of the file.

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9-9: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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11-11: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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16-16: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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21-21: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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22-22: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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31-31: LGTM!

The update to the print statement to use an f-string improves readability and performance. Although not directly related to the PR objective, it's a good improvement.

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37-39: LGTM!

The calculation of the accuracy score using the accuracy_score function from sklearn.metrics is relevant to the PR objective. The accuracy score is calculated correctly by comparing the actual and predicted reading levels, and is logged correctly using an f-string.

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41-43: LGTM!

Writing the accuracy score to a separate text file (step3_2_accuracy_score.txt) is a good practice for easy access and reference. The accuracy score is correctly converted to a string before writing to the file.

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Line range hint 1-43: Great job on this PR!

The changes in this file are well-structured and easy to follow. The file achieves the primary objective of calculating and logging the accuracy score, which is relevant to the linked issue. The accuracy score is calculated correctly using the accuracy_score function from sklearn.metrics and is written to a separate text file for easy access and reference.

In addition to the accuracy score calculation, the file also includes other relevant functionality such as loading the PMML model and test data, making predictions, and calculating the mean absolute error. The print statements throughout the file have been updated to use f-strings, which improves readability and performance.

Overall, the changes in this PR are a valuable addition to the project and align with the linked issue's objectives. Keep up the good work!

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