What is Predictive Analytics?

Predictive Analytics is the sub-branch of Advanced Analytics, the key area of Data Science that uses Statistical concepts to output the maximum likelihood of an event to happen. Mathematics and Statistics are the building blocks of Predictive Analytics. It looks into the historical data and finds the trends & patterns from it by using the statistics and build the strategy to apply on new data to compute and predict the best possible outcomes. It is not only based on statistical terms but also a combination of Data mining that provides Knowledge Discovery and Data-Driven features related to the prediction. You may also learn more about Cognitive Analytics in this insight.

Types of Predictive Analytics

Based on the computation strategy, Predictive Analytics broadly classified into two classes –

Statistical/Mathematical Modelling

This approach of modeling uses the Equation-Based models that describe the whole phenomenon under consideration. Example : Time-Series Regression and Linear Regression.

Computational Modelling

This modeling relies on the models that are not easy to explain in the form of the equation and often requires the simulation of the built functions for making the prediction called ‘Black-Box Prediction Modelling’ because the model structure does not provide the insights into factors that can map models Inputs to outputs. Example: Neural Networks.

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