Anomaly Detection from available sensor data set?

Question

I am working on a live sensor data set and looking for abnormal patterns (leading to a machine fault condition) from the available data set.

I am learning and new to the world of data science, but comfortable with Python. I have few questions that I am looking to get suggestions.

1. What kind of algorithms would be best suited for this case?
2. What are the basic steps for doing a predictive analysis in python?

Please correct me if my questions are not correctly framed.

Answer 1

You are talking about anomaly detection, and there are many approaches. If you can create a training set, one-class SVM is a place to start, but even simple control charts can be useful, particularly with live streaming data.

Answer 2

If you have a dataset with labeled anomalies, then you can use a binary classification approach. If the anomalies are not labeled, then you have to look into outlier/novelty detection. The scikit-learn documenation has a good overview.