Predictive modeling uses known results to create, process, and validate a model to forecast future outcomes. It is a tool used in predictive analytics , a data mining technique.

Image: max_776/Adobe Stock. Predictive modeling is a type of data mining that is used in a variety of situations and industries. This process involves creating statistical models that can make ...

Key Points Predictive analytics allows for proactive decision-making, as opposed to reacting when things go wrong. Utilizing ...

Predictive modeling solutions frequently use data mining technologies to analyze large sets of data. Common steps in the predictive modeling process include gathering data, performing statistical ...

No-one has time to flip through a 200 page pdf to find the information they seek these days, and so it is that healthcare data and clinical electronic health records (EHRs) have come into play.

It provides predictive analytics, data mining, machine learning, forecasting, optimization, and text analytic model capabilities to help organizations make decisions based on data.

This article provides a quick explanation of the nine most common data-mining techniques used in predictive analytics. Becoming familiar with them will go a long way toward enabling you to recognize ...

The output of any data model is only as good as its input. To find and understand audiences at scale, a model needs to be fed a data set that’s large enough and truly representative of the overall ...

Generating a predictive model can take hours using traditional data science methods. But Pecan enables analysts to quickly iterate and experiment by shortening that time to 15 minutes or less.

Predictive analytics can be traced back to early statistical models and data mining techniques, which laid the groundwork for modern data-driven decision-making.