<p>If you are OK to use python, thy novelty-detection with sklearn:</p>

<p><a href="https://scikit-learn.org/stable/modules/outlier_detection.html" rel="nofollow noreferrer">https://scikit-learn.org/stable/modules/outlier_detection.html</a></p>

CC BY-SA 4.0
2019-03-18T10:20:14.817Z
I tried this but the results are not that convincing
Abishek
CC BY-SA 4.0
2019-03-14T09:56:03.567Z
2019-03-14T09:56:03.567Z
Vivek
<p><a href="https://numenta.org" rel="nofollow noreferrer">Hierarchical Temporal Memory</a> is a model <a href="https://numenta.com/assets/pdf/whitepapers/Numenta%20White%20Paper%20-%20Science%20of%20Anomaly%20Detection.pdf" rel="nofollow noreferrer">well suited for anomaly detection</a>. It is also pretty interesting and different from currently typical Deep Learning models. </p>

CC BY-SA 4.0
2019-03-14T10:44:35.133Z
I would add the detail that HTM-based algorithms are better suited for cases where you expect a stream of data (i.e. you want to continuously learn and detect anomalies online).
nbro
CC BY-SA 4.0
2019-03-14T09:56:20.197Z
2019-03-14T09:56:20.197Z
BlindKungFuMaster
<p>I need to create model which will find suspicious entries or anomalies in a network, whose characteristics or features are the <code>asset_id</code>, <code>user_id</code>, IP accessed from and <code>time_stamp</code>.</p>

<p>Which unsupervised anomaly detection algorithms or models should I use to solve this task?</p>

<unsupervised-learning><anomaly-detection>
Which unsupervised anomaly detection algorithms are there?
Abishek
# Which unsupervised anomaly detection algorithms are there?

(Asked by: username_0 on 2019-03-14)

I need to create model which will find suspicious entries or anomalies in a network, whose characteristics or features are the `asset_id`, `user_id`, IP accessed from and `time_stamp`.

Which unsupervised anomaly detection algorithms or models should I use to solve this task?

**Tags:** unsupervised-learning, anomaly-detection


---

## 2 answers

### Answer by username_1 on 2019-03-14. Score: 1 | Accepted answer

If you are OK to use python, thy novelty-detection with sklearn:

<https://scikit-learn.org/stable/modules/outlier_detection.html>

> **Comments:**
> **username_0**: I tried this but the results are not that convincing  

---

### Answer by username_2 on 2019-03-14. Score: 1

[Hierarchical Temporal Memory](https://numenta.org) is a model [well suited for anomaly detection](https://numenta.com/assets/pdf/whitepapers/Numenta%20White%20Paper%20-%20Science%20of%20Anomaly%20Detection.pdf). It is also pretty interesting and different from currently typical Deep Learning models.

> **Comments:**
> **username_3**: I would add the detail that HTM-based algorithms are better suited for cases where you expect a stream of data (i.e. you want to continuously learn and detect anomalies online).  

---

