Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Anomaly Detection in Time Series #987

Merged
merged 12 commits into from
Nov 10, 2024
Merged

Conversation

alo7lika
Copy link
Contributor

Pull Request for DL-Simplified 💡

Issue Title: Anomaly Detection in Time Series

  • Info about the related issue (Aim of the project): To develop an effective model for detecting anomalies in time series data, leveraging LSTM networks for improved accuracy and reliability.
  • Name: Alolika Bhowmik
  • GitHub ID: alolikabhowmik
  • Email ID: alolikabhowmik72@gmail.com
  • Identify yourself: GSSoC Contributor

Closes: #967

Describe the add-ons or changes you've made 📃

I have added a model for anomaly detection in time series using LSTM networks. The model uses a synthetic dataset to identify and classify anomalies effectively, and I have also implemented additional models like Facebook Prophet and Isolation Forest for comparison.

Type of change ☑️

What sort of change have you made:

  • New feature (non-breaking change which adds functionality)
  • This change requires a documentation update

How Has This Been Tested? ⚙️

The models have been tested using accuracy scores and classification metrics on the synthetic dataset. I also validated results through exploratory data analysis (EDA) and cross-checked predictions for anomaly classification.

Checklist: ☑️

  • My code follows the guidelines of this project.
  • I have performed a self-review of my own code.
  • I have commented my code, particularly wherever it was hard to understand.
  • I have made corresponding changes to the documentation.
  • My changes generate no new warnings.
  • I have added things that prove my fix is effective or that my feature works.
  • Any dependent changes have been merged and published in downstream modules.

Copy link

Our team will soon review your PR. Thanks @alo7lika :)

@alo7lika
Copy link
Contributor Author

@abhisheks008 ASSIGN THE LABEL " GSSOC-EXT" AND LEVEL ON THE PR AS WELL AS ON THE ISSUE PAGE AND REVIEW IT

@alo7lika
Copy link
Contributor Author

@abhisheks008 ASSIGN THE LABEL " GSSOC-EXT" AND LEVEL ON THE PR AS WELL AS ON THE ISSUE PAGE AND REVIEW IT

Also assign the task to me , you haven't assigned it

Copy link
Owner

@abhisheks008 abhisheks008 left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Approved and level upgraded.
@alo7lika

@abhisheks008 abhisheks008 added Status: Approved Approved PR by the PA. level 3 Level 3 for GSSOC gssoc-ext labels Nov 10, 2024
@abhisheks008 abhisheks008 merged commit a1d16c0 into abhisheks008:main Nov 10, 2024
1 check passed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
gssoc-ext level 3 Level 3 for GSSOC Points Updated Status: Approved Approved PR by the PA.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Anomaly Detection in Time Series
2 participants