Add ART1 algorithm in neural network

[JeninaAngelin]

Feature description

Description:

This issue aims to implement an Adaptive Resonance Theory (ART1) algorithm for binary data clustering. ART1 is well-suited for unsupervised learning with binary inputs, using a vigilance parameter to determine the clustering threshold. This model will enhance the framework's clustering capabilities, allowing for pattern recognition in binary data.

Goals:

Implement an ART1 class with training and prediction functionalities.

Allow the user to specify the vigilance parameter to control cluster formation.

Include a similarity calculation and weight adjustment function.

Requirements:

Initialization: ART1 class should initialize with num_features and vigilance.

Training: Implement a train(data) method to cluster binary data based on the vigilance parameter.

Prediction: Add a predict(x) method to classify new input into an existing cluster or mark it as a new cluster if it does not match any.

Documentation: Include docstrings and usage examples to clarify the purpose of each method.

Testing: Provide example usage for verification and add unit tests to confirm functionality.

[Vraj2811]

Hi @JeninaAngelin, I would like to work upon this
I am new to open-source

Can you please help me with how do I get started ?

[JeninaAngelin]

Actually I tried adding code for the ART network algorithm but sadly it didn't pass the required tests.

You can work by asking the repo owner to assign this issue to you or create a PR fixing the issue.