Emily Moody
Published: 2014
Total Pages: 70
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Predictive systematic computational analysis of data or statistics surrounds a diversity of methods as of numbers, depicting, engine educating, and information mining that examine present and past details to create forecasts regarding time to come, either else unidentified, happenings. There has never been a Predictive Analytics Guide like this. It contains 90 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Predictive Analytics. A quick look inside of some of the subjects covered: Predictive analytics Applications, Predictive analytics Fraud detection, Predictive analytics Definition, Predictive analytics Clinical decision support systems, Predictive analytics Customer retention, Text analytics, Predictive analytics Cross-sell, Predictive analytics Tools, JMP (statistical software) History, Business intelligence, Text mining, Fraud - Detection, Apache Hadoop Commercially supported Hadoop-related products, Business process management BPM suites, Intelligent text analysis - Commercial, Google privacy - Ties to the CIA and NSA, Data mining, Data analysis, Oracle Data Mining - References and further reading, Oracle Data Mining - Graphical user interface: Oracle Data Miner, Predictive analytics Further reading, Business intelligence Applications in an enterprise, Data mining Research and evolution, Predictive analytics Portfolio, product or economy-level prediction, Predictive analytics Regression techniques, Predictive analytics Machine learning techniques, Predictive analytics Analytical Techniques, Analytics - Challenges, Oracle Data Mining - Overview, SAS (software), RapidMiner, R (programming language), and much more...