Dear,
I have been try to analyze the IoT sensor data using clustering algorithms by considering data sets. can you suggest, which clustering approach suites for the cluster data analysis in incremental way.
KNN
https://stackoverflow.com/questions/4274218/incremental-nearest-neighbor-algorithm-in-python
There are many algorithms and it depends on what the data looks like (i.e. moon shaped, box, circle, linear, non-linear). Once the data understood then a choice of algorithms would be selected such as near-neighbor, k-means, etc.
Sivadi Balakrishna It all depends on the type of data you have, features set and your assumptions. A lot of tools employ unsupervised models without understanding the underlying assumptions. Also, it depends on what kind of analysis you plan to do. For example anomaly detection, fault classification etc.
If you are anomaly detection, please read this paper
Amruthnath, Nagdev, and Tarun Gupta. "A research study on unsupervised machine learning algorithms for early fault detection in predictive maintenance." In 2018 5th International Conference on Industrial Engineering and Applications (ICIEA), pp. 355-361. IEEE, 2018.
If you are planning to fault classification in unsupervised way, please read this paper
Amruthnath, Nagdev, and Tarun Gupta. "Fault class prediction in unsupervised learning using model-based clustering approach." In 2018 International Conference on Information and Computer Technologies (ICICT), pp. 5-12. IEEE, 2018.
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