Reimplement polynomial_regression.py

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

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[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

algorithms-keeper actions can be triggered by commenting on this PR:

• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

algorithms-keeper actions can be triggered by commenting on this PR:

• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

algorithms-keeper actions can be triggered by commenting on this PR:

• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

algorithms-keeper actions can be triggered by commenting on this PR:

• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

algorithms-keeper actions can be triggered by commenting on this PR:

• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.

[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

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[tianyizheng02]

Describe your change:

Contributes to #6216

• Reimplemented machine_learning/polynomial_regression.py using numpy because the old original implementation was just a how-to on doing polynomial regression using sklearn
• Added detailed function documentation, doctests, and algorithm explanation
• Fixed typo in file name: polymonial_regression.py -> polynomial_regression.py

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> np.allclose(poly_reg.params, coefs, atol=10e-5)
Expected:
True
Got:
False

This doctest passes when I run it locally on my own machine, so I'm guessing the failure here is due to some variation in numpy's calculations on different systems

[tianyizheng02]

=================================== FAILURES ===================================
__ [doctest] machine_learning.polynomial_regression.PolynomialRegression.fit ___
133 Traceback (most recent call last):
134 ...
135 ArithmeticError: Design matrix is not full rank, can't compute coefficients
136 137 Make sure errors don't grow too large:
138 >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1])
139 >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs
140 >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1)
141 >>> poly_reg.fit(x, y)
142 >>> poly_reg.params # Output params for debugging
Expected nothing
Got:
array([-250.0000132 , 50.00017691, -2.00040817, 36.00038528,
19.99980068, -11.99993801, 9.99998778, 2.00000153,
-1.00000012, -14.99999999, 1. ])

The estimated parameters clearly are close to the true parameters, so I'll just set the tolerance to a larger value.

[CaedenPH]

Very nice documentation about each function

[algorithms-keeper]

Click here to look at the relevant links ⬇️

🔗 Relevant Links

Repository:

• Contributing guidelines
• Project Euler solution guidelines

Python:

• Formatted string literals (f-strings)
• Type hints
• doctest
• unittest
• pytest

Automated review generated by algorithms-keeper. If there's any problem regarding this review, please open an issue about it.

---

algorithms-keeper commands and options

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• @algorithms-keeper review to trigger the checks for only added pull request files
• @algorithms-keeper review-all to trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.

NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.