docs(synthetic): add dataset overview table

examples/synthetic_data_streams/README.md

@@ -9,6 +9,25 @@ The following synthetic datasets are currently available:
 - Sine1, Sine2, Mixed, Stagger, Circles, LED [[Link]](https://github.com/alipsgh/data-streams)  
 - SEA, Hyperplane [[Link]](https://www.win.tue.nl/~mpechen/data/DriftSets/)
 
+| Dataset    | # Instances | # Features | # Classes | Drift type           |
+|------------|-------------|------------|-----------|----------------------|
+| Sine1      | 100.000     | 2          | 2         | Sudden               |
+| Sine2      | 100.000     | 2          | 2         | Sudden               |
+| Mixed      | 100.000     | 4          | 2         | Sudden               |
+| Stagger    | 100.000     | 3          | 2         | Sudden               |
+| Circles    | 100.000     | 2          | 2         | Gradual              |
+| LED        | 100.000     | 24         | 10        | Sudden               |
+| SEA        | 50.000      | 3          | 2         | Sudden               |
+| Hyperplane | 10.000      | 10         | 2         | Gradual; Incremental |
+
+_Characteristics of datasets used, see the survey [Learning under Concept Drift: A Review](https://arxiv.org/pdf/2004.05785.pdf) for more information._
+
+For the sudden-drift datasets, the drifting point is centred at every 5th of the instances for Sine1, Sine2 and Mixed and at each 3rd for Stagger, for a transition over 50 samples. 
+For the remaining gradually shifting datasets, Circles and LED, the drifting point is centred around every 4th, and takes place over 500 instances. 
+A noise level of 10\% is added to each dataset. 
+ where the drifting points occur at each 4th. 
+The shift in The Hyperplane dataset that was used, consists of 10.000 samples, and the drift is incremental and gradual.
+
 (adding other datasets will be simple based on the available reference configuration)
 
 ## Getting started