Predicts users' and Systems' Behavior

Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.

We use two types of predictive models. Classification models predict class membership. For instance, you try to classify whether someone is likely to leave, whether he will respond to a solicitation, whether he’s a good or bad credit risk, etc. Usually, the model results are in the form of 0 or 1, with 1 being the event you are targeting. Regression models predict a number – for example, how much revenue a customer will generate over the next year or the number of months before a component will fail on a machine.

For extremely complex relationships, Neural networks are sophisticated techniques capable of modeling such challenges like non linear relationship in data that increases overtime. Other types of analysis and models may be used, like Bayesian analysis, Decision trees, Ensemble models, KNN, TS models, etc