![]() ![]() Predictive analytics adopters have easy access to a wide range of statistical, data-mining and machine-learning algorithms designed for use in predictive analysis models. On the cutting edge of predictive analytics techniques are neural networks - algorithms designed to identify underlying relationships within a data set by mimicking the way a human mind functions. Regression helps users forecast asset values and comprehend the relationships between variables, such as commodities and stock prices. Regression techniques are often used in banking, investing, and other finance-oriented models. The branching method can also show every possible outcome of a particular decision and how one choice may lead to the next. ![]() Many methods are unique to specific products and services, but a core of generic techniques, such as decision trees, regression - and even neural networks - are now widely supported across a wide range of predictive analytics platforms.ĭecision trees, one of the most popular techniques, rely on a schematic, tree-shaped diagram that’s used to determine a course of action or to show a statistical probability. Model users have access to an almost endless range of predictive modeling techniques. ![]()
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