Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner

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Put Predictive Analytics into Actions Find out the fundamentals of Predictive Evaluation and Data Mining via an easy to comprehend conceptual framework and instantly practice the concepts discovered using the open up source RapidMiner device. Data Mining is becoming an essential device for any business that collects, shops and processes data within its functions. Whether you are completely new to Data Mining or focusing on your tenth task, this book will highlight how exactly to analyze data, uncover concealed patterns and romantic relationships to aid essential decisions and predictions. This reserve is fantastic for business users, data analysts, business analysts, business cleverness and data warehousing experts and for anyone who would like to find out Data Mining. You’ll have the ability to: 1. Gain the required understanding of different data mining methods, to enable you to select the right way of a given data issue and create an over-all purpose analytics process. 2. 3. Get right up and working fast with an increase of than two dozen typically used effective algorithms for predictive analytics using useful use cases.LearnPredictiveAnalytics. Execution files could be downloaded from the publication companion site at www. Implement a straightforward step-by-step procedure for predicting an end result or discovering hidden associations from the info using RapidMiner, an open up source GUI structured data mining device

Predictive analytics and Data Mining methods covered: Exploratory Data Evaluation, Visualization, Decision trees, Guideline induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Systems, Support Vector devices, Ensemble models, Bagging, Improving, Random Forests, Linear regression, Logistic regression, Association evaluation using Apriori and FP Development, K-Means clustering, Density structured clustering, Personal Organizing Maps, Textual content Mining, Period series forecasting, Anomaly recognition and show selection.com

• Demystifies data mining principles with easy to comprehend vocabulary
• Shows ways to get ready to go fast with 20 commonly used powerful approaches for predictive evaluation
• Explains the procedure of using open resource RapidMiner equipment
• Discusses a straightforward 5 step procedure for implementing algorithms which you can use for executing predictive analytics
• Includes practical use cases and good examples

See also

• Artificial Intelligence: What Everyone Needs to Know
• Superintelligence: Paths, Dangers, Strategies
• Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (The MIT Press)