In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:

1. Trend analysis
2. Outlier/anomaly detection
3. Examining shocks/unexpected variation
4. Association analysis
5. Forecasting
6. Predictive analytics

Here I am focusing on outlier…

Summary: Unless you’re involved in anomaly detection you may never have heard of Unsupervised Decision Trees.  It’s a very interesting approach to decision trees that on the surface doesn’t sound possible but in practice is the backbone of modern intrusion detection.

I was at a presentation recently that focused on stream processing but the use case presented was about anomaly detection.  When they started talking about unsupervised decision trees my…

Summary:  Dealing with imbalanced datasets is an everyday problem.  SMOTE, Synthetic Minority Oversampling TEchnique and its variants are techniques for solving this problem through oversampling that have recently become a very popular way to improve model performance.

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With the online holiday shopping season heavily underway and expected to reach $83 billion this year, online stores need to run smoothly, including having prices in order. It may sound basic, but simple computer glitches can cause pricing errors that may excite consumers, but cause major problems down the line. For example, for a few hours this summer, visitors…