* Added Opertation for triangular fuzzy sets
* Added Sources
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* Fix the bug in fuzzy_operations.py & deleted test
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* Again done
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* Fix
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* Fixed the bug, made a FuzzySet dataclass
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* added excess-3 code
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* Added Gradient Boosting Classifier
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* [ADD] tests for odd_even_transposition_parallel
* adding another test because build failed 6 hrs
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* [1, 32.0, 9] test uncommented
* [-442, -98, -554, 266, -491, 985, -53, -529, 82, -429] test uncommented
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* Add new algorithm index_2d_array_in_1d
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* Update cocktail_shaker_sort.py
Added a docstring with clear explanations of the function and its parameters.
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Adjusted the loop ranges to make the code more concise and readable.
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Provided a clear message when printing the sorted list.
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* Added test case for tuple
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* Added Lens formulae to the Physics repository
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* added mean absolute error to loss_functions.py
* added doctest to mean absolute error to loss_functions.py
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* fixed error in MAE
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* Add error tests in doctest and fix error message
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* added mean absolute percentage error
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* Code Enhancements in merge_sort.py
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* Improved Equilibrium Index of an Array.
This is the modifications made to the original code:
1. Create Doctest Instructions: Python "doctest" can be executed by running the following command: python -m doctest -v equilibrium_index.py.
2. Deleted Argument {size}: Deleted the `size` argument because `len(arr)} allows the array's length to be determined inside the function, simplifying and improving the readability of the function signature.
3. Used {enumerate}: To improve code readability and indicate that we're working with element-index pairs, we iterated through the array using both elements and their indices using the `enumerate` function.
4. Optimized the Loop: To prevent pointless additions, the loop was improved by initializing {left_sum} with the value of the first element (arr[0]). Furthermore, since the beginning and last items (0 and size - 1) cannot be equilibrium indices, there is no need to check them, saving further computations.
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* Code enhancements in binary_insertion_sort.py
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* Add function docstrings, comments and type hints
* Fix type mismatch
* Fix type hint error
* Fix float to int error
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* Tried new TESTS for the binomial_coefficient
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* import requests
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* Add `Invert a Binary Tree` solution
* Add type
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* Add New Algorithm: Triangular Numbers
* Calculate nth triangular number instead of generating a list
* Handle 0th position and update function name and docstring
* Add Simple Moving Average (SMA) Calculation
This commit adds a Python script for calculating the Simple Moving Average (SMA) of a time series data.
The script also includes a doctest that verifies the correctness of the SMA calculations for a sample dataset.
Usage:
- Run the script with your own time series data and specify the window size for SMA calculations.
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