Feature request: Add Anomaly Detection Project

[sanchitc05]

Currently, our project repository lacks a comprehensive anomaly detection project. This limits our ability to explore advanced data mining techniques and real-world applications.

Description
This project aims to identify unusual patterns in data, such as fraudulent transactions or network intrusions. We will leverage techniques like clustering and isolation forests to detect anomalies.

We propose adding an anomaly detection project to our repository. This project will cover the following:

• Data collection and preprocessing
• Exploratory Data Analysis (EDA)
• Anomaly detection techniques (clustering, isolation forests)
• Model evaluation
• Data visualization

We could consider other anomaly detection techniques like one-class SVM or statistical methods, but for a comprehensive project, a combination of clustering and isolation forests is a good starting point.

Approach to be followed

1. Data Collection and Preprocessing: Gather a relevant dataset (e.g., financial transactions, network logs) and preprocess it to handle missing values and outliers.
2. Exploratory Data Analysis (EDA): Visualize data distributions, identify potential anomalies, and calculate summary statistics.
3. Anomaly Detection Techniques:
   • Clustering-based methods: Group similar data points and identify outliers.
   • Isolation Forest: Isolate anomalous data points by randomly partitioning the data space.
4. Model Evaluation: Evaluate the performance of the anomaly detection techniques using appropriate metrics.
5. Data Visualization: Visualize the detected anomalies to gain insights.

Additional context

This project will provide valuable insights into anomaly detection techniques and their applications in various domains. It will also help us strengthen our data mining, machine learning, and data visualization skills.

[github-actions]

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[github-actions]

Hello @sanchitc05! Your issue #858 has been closed. Thank you for your contribution!

[github-actions]

Hello @sanchitc05! Your issue #858 has been closed. Thank you for your contribution!