Difference between revisions of "...find outliers"
m |
m |
||
| Line 25: | Line 25: | ||
*** [[Autoencoder (AE) / Encoder-Decoder]] | *** [[Autoencoder (AE) / Encoder-Decoder]] | ||
*** [[Radial Basis Function Network (RBFN)]] | *** [[Radial Basis Function Network (RBFN)]] | ||
| − | |||
* [http://en.wikipedia.org/wiki/Outlier Outlier | Wikipedia] | * [http://en.wikipedia.org/wiki/Outlier Outlier | Wikipedia] | ||
* [http://medium.com/@srnghn/machine-learning-trying-to-detect-outliers-or-unusual-behavior-2d9f364334f9 Machine Learning: Trying to detect outliers or unusual behavior | Stacey Ronaghan - Medium] | * [http://medium.com/@srnghn/machine-learning-trying-to-detect-outliers-or-unusual-behavior-2d9f364334f9 Machine Learning: Trying to detect outliers or unusual behavior | Stacey Ronaghan - Medium] | ||
| Line 34: | Line 33: | ||
** [[Signals]] | ** [[Signals]] | ||
** [[Pathology]] | ** [[Pathology]] | ||
| + | |||
<hr><center> | <hr><center> | ||
Revision as of 15:32, 20 March 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- AI Solver
- Looking for event based?
- Do you have > 100 features?
- Yes, then try One-class Support Vector Machine (SVM)
- No, need fast training, then try Principal Component Analysis (PCA)-based Anomaly Detection
- Also consider...
- Outlier | Wikipedia
- Machine Learning: Trying to detect outliers or unusual behavior | Stacey Ronaghan - Medium
- Outlier Detection and Removal Algorithm in K-Means and Hierarchical Clustering | A. Barai and L. Dey
- Capabilities ... Search ... Clustering ... Recommendation ... Anomaly Detection ... Classification ... Dimensional Reduction ... ...find outliers
Outliers don't necessarily represent abnormal behavior
An Outlier is a rare chance of occurrence within a given data set. In Data Science, an Outlier is an observation point that is distant from other observations. An Outlier may be due to variability in the measurement or it may indicate experimental error. Outliers, being the most extreme observations, may include the sample maximum or sample minimum, or both, depending on whether they are extremely high or low. However, the sample maximum and minimum are not always outliers because they may not be unusually far from other observations. - Outlier Detection and Anomaly Detection with Machine Learning | Mehul Ved - Medium
