Predictive Analytics and Data Mining: Concepts and Practice with RapidMinerКНИГИ » ПРОГРАММИНГ
Название: Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner Автор: Vijay Kotu, Bala Deshpande Издательство: Elsevier Год: 2015 Формат: PDF Для сайта:Mirknig.su Страниц: 426 Размер: 10,41 МБ Язык: English
Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. You’ll be able to: 1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process. 2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases. 3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool
Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Na?ve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com
Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples
Уважаемый посетитель, Вы зашли на сайт как незарегистрированный пользователь.
С этой публикацией часто скачивают:
Data Science: Concepts and Practice 2nd Edition Название: Data Science: Concepts and Practice Second Edition Автор: by Vijay Kotu, Bala Deshpande Издательство: Morgan Kaufmann Год: 2018 Формат:...
Exploring Data with RapidMiner Автор: Andrew Chisholm Название: Exploring Data with RapidMiner Издательство: Packt Publishing Год: 2013 ASIN: B00GX67U0I Язык: English Формат: epub...
Data Analytics and Linux Operating System Название: Data Analytics and Linux Operating System Автор: Isaac D. Cody Издательство: CreateSpace Independent Publishing Platform Год: 2016 Страниц:...
Business Analytics Using R - A Practical Approach Название: Business Analytics Using R - A Practical Approach Автор: Umesh Hodeghatta Rao Издательство: Apress Год: 2017 Страниц: 266 Формат: PDF...
Навигация
Вход на сайт
Реклама
Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner 
