Fixes #19 by Implemented Buy/Sell Recommendation System with K-Means Clustering and Silhouette Score Evaluation

[kundana29]

Fixes #19

• Added K-Means clustering to classify stock price data into Buy, Sell, and Hold signals based on technical indicators such as Returns, Moving Averages (MA_50 and MA_200), and Volatility.
• Integrated a backtesting system to simulate trades based on the generated buy/sell signals and calculated final portfolio value.
• Evaluated the clustering quality using the Silhouette Score and optimized the number of clusters using the Elbow Method.
• Enhanced the feature set by calculating additional indicators like MACD and incorporated them into the clustering model.
• Plotted the buy/sell signals on historical stock data to visually validate the system's performance.

[github-actions]

Ensure the PR matches the requirements mentioned in the Contribution guide. The maintainer might get in touch to enusre quality. Thanks for your time

[Mayureshd-18]

@kundana29 What's the issue number that you have been assigned? If not please create one first else please link the issue using keywords. (fixes/closes..) You can find the detailed info about the same here:
https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword

Thanks & regards.

[kundana29]

@Mayureshd-18 I am working on issue #19 . Clustering Algorithms for Buy/Sell Recommendation System .

[Mayureshd-18]

@kundana29 Please use the keywords as mentioned in the docs as they are. Then only your issue will be linked to the PR. If needed please refer to other PRs which have issues linked to them.

Thanks and Regards

[Mayureshd-18]

Lgtm!