Add artificial_neural_network.py in neural_network #11858
Conversation
algorithms-keeper
bot
added
awaiting reviews
![algorithms-keeper[bot]](https://avatars.githubusercontent.com/in/235834?s=60&v=4){kind=small}
There was a problem hiding this comment.
Click here to look at the relevant links ⬇️
🔗 Relevant Links
Repository:
Python:
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 reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto 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.
| """Sigmoid activation function.""" | ||
| return 1 / (1 + np.exp(-x)) | ||
|
|
||
| def sigmoid_derivative(self, x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/artificial_neural_network.py, please provide doctest for the function sigmoid_derivative
Please provide return type hint for the function: sigmoid_derivative. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide descriptive name for the parameter: x
Please provide type hint for the parameter: x
| """Derivative of the sigmoid function.""" | ||
| return x * (1 - x) | ||
|
|
||
| def feedforward(self, x): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/artificial_neural_network.py, please provide doctest for the function feedforward
Please provide return type hint for the function: feedforward. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide descriptive name for the parameter: x
Please provide type hint for the parameter: x
| self.final_output = self.sigmoid(self.final_input) | ||
| return self.final_output | ||
|
|
||
| def backpropagation(self, x, y, output): |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/artificial_neural_network.py, please provide doctest for the function backpropagation
Please provide return type hint for the function: backpropagation. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide descriptive name for the parameter: x
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: y
Please provide type hint for the parameter: y
Please provide type hint for the parameter: output
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
Simple Artificial Neural Network (ANN) Implementation
Description:
This PR adds a basic implementation of a feedforward Artificial Neural Network (ANN) using Python and NumPy. The network consists of one hidden layer and uses Sigmoid activation, backpropagation with gradient descent, and Mean Squared Error (MSE) as the loss function. It demonstrates a solution to the XOR problem, commonly used in introductory neural network tutorials.
Key Features:
Checklist:
Checklist: