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Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637

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Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
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ank426:master

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@ank426ank426 commented Oct 17, 2023

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Describe your change:

I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.

  • 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".

@algorithms-keeperalgorithms-keeperBot added tests are failing Do not merge until tests pass and removed tests are failing Do not merge until tests pass labels Oct 17, 2023
@cclauss

cclauss commented Oct 17, 2023•
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.

The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.

Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?

@cclausscclauss mentioned this pull request Oct 17, 2023
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@algorithms-keeperalgorithms-keeperBot mentioned this pull request Oct 18, 2023
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@tianyizheng02

tianyizheng02 commented Oct 18, 2023

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?

Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.

@ank426

ank426 commented Oct 19, 2023

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?

Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.

Hey so could you please accept the PR, or are there any changes I have to make?

@tianyizheng02
tianyizheng02 merged commit bd3072b into TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02 mentioned this pull request Oct 20, 2023
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@isidroasisidroas mentioned this pull request Jan 25, 2025
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
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@ank426
@ank426ank426
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Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
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Oct 17, 2023
 Merged

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
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Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Conversation
@ank426
@ank426ank426
commented
Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
 Merged

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
commented
Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
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TheAlgorithms:masterfrom 
ank426:master
Conversation
@ank426
@ank426ank426
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Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
 Merged

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@algorithms-keeperalgorithms-keeperBot
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@tianyizheng02
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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
commented
Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
mentioned this pull request
Oct 20, 2023
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
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TheAlgorithms:masterfrom 
ank426:master
Conversation
@ank426
@ank426ank426
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Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
 Merged

14 tasks
@algorithms-keeperalgorithms-keeperBot
mentioned this pull request
Oct 18, 2023
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@tianyizheng02
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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
commented
Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
mentioned this pull request
Oct 20, 2023
 Merged

15 tasks
@isidroasisidroas
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Jan 25, 2025
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
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Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
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tianyizheng02 merged 3 commits into
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ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
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@ank426
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Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
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@tianyizheng02
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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
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Oct 19, 2023

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
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Oct 20, 2023
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@isidroasisidroas
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Conversation
@ank426
@ank426ank426
commented
Oct 17, 2023

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Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
@algorithms-keeperalgorithms-keeperBot
added

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@cclauss
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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
 Merged

14 tasks
@algorithms-keeperalgorithms-keeperBot
mentioned this pull request
Oct 18, 2023
 Closed

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@tianyizheng02
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Oct 18, 2023

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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
commented
Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
mentioned this pull request
Oct 20, 2023
 Merged

15 tasks
@isidroasisidroas
mentioned this pull request
Jan 25, 2025
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Added Mean Squared Logarithmic Error (MSLE) Loss Function by ank426 · Pull Request #10637 · TheAlgorithms/Python · GitHub
Skip to content
Added Mean Squared Logarithmic Error (MSLE) Loss Function - #10637
Merged
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Oct 19, 2023
Merged
Added Mean Squared Logarithmic Error (MSLE) Loss Function#10637
tianyizheng02 merged 3 commits into
TheAlgorithms:masterfrom 
ank426:master
Conversation
@ank426
@ank426ank426
commented
Oct 17, 2023

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Contributor
Describe your change:
I have added MSLE loss function which is very useful when dealing with regression problems involving skewed or large-value targets.
  •  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".
@algorithms-keeperalgorithms-keeperBot
added

tests are failing
Do not merge until tests pass
and removed

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@cclauss
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Oct 17, 2023•

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This directory of loss functions is less compelling than I thought because each is three lines or less of algorithmic code.
The files are about 100 lines long with comments, doctests, validation code, and other boilerplate. It takes a lot of clicking in and out of files to review all of the various loss functions.
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
@cclausscclauss
mentioned this pull request
Oct 17, 2023
 Merged

14 tasks
@algorithms-keeperalgorithms-keeperBot
mentioned this pull request
Oct 18, 2023
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@tianyizheng02
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Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
@ank426
ank426
commented
Oct 19, 2023

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ContributorAuthor
Would we be better off making a single loss_functions.py that contains all these functions so that they can be studied side-by-side without all the opening and closing of files?
Sounds good to me. Once we're done handling the existing loss function PRs we can open a new PR to consolidate all of the loss functions.
Hey so could you please accept the PR, or are there any changes I have to make?
@tianyizheng02
tianyizheng02
merged commit bd3072b
into
TheAlgorithms:masterOct 19, 2023
@tianyizheng02tianyizheng02
mentioned this pull request
Oct 20, 2023
 Merged

15 tasks
@isidroasisidroas
mentioned this pull request
Jan 25, 2025
 Closed

14 tasks
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