Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner (Paperback)
暫譯: 預測分析與資料探勘：RapidMiner 的概念與實務 (平裝本)

Vijay Kotu, Bala Deshpande

Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner (Paperback)

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商品描述

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, Naïve 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

商品描述(中文翻譯)

**將預測分析付諸實行**
透過易於理解的概念框架學習預測分析和資料探勘的基本知識，並立即使用開源工具 RapidMiner 實踐所學的概念。無論您是資料探勘的新手還是正在進行第十個專案，本書將教您如何分析數據，揭示隱藏的模式和關係，以協助重要的決策和預測。資料探勘已成為任何收集、儲存和處理數據的企業運營中不可或缺的工具。本書非常適合商業用戶、數據分析師、商業分析師、商業智慧和數據倉儲專業人士，以及任何想學習資料探勘的人。您將能夠：

1. 獲得不同資料探勘技術的必要知識，以便為特定的數據問題選擇合適的技術並創建通用的分析流程。
2. 快速上手，使用超過二十種常用的強大算法進行預測分析，並透過實際案例進行練習。
3. 使用 RapidMiner 這個基於 GUI 的開源資料探勘工具，實施一個簡單的逐步過程來預測結果或從數據中發現隱藏的關係。

涵蓋的預測分析和資料探勘技術：探索性數據分析、視覺化、決策樹、規則歸納、k-最近鄰、朴素貝葉斯、人工神經網絡、支持向量機、集成模型、袋裝法、提升法、隨機森林、線性回歸、邏輯回歸、使用 Apriori 和 FP Growth 的關聯分析、K-Means 聚類、基於密度的聚類、自組織映射、文本探勘、時間序列預測、異常檢測和特徵選擇。實作檔案可從本書伴隨網站 www.LearnPredictiveAnalytics.com 下載。

- 用易於理解的語言解釋資料探勘概念
- 展示如何快速上手使用 20 種常用的強大預測分析技術
- 解釋使用開源 RapidMiner 工具的過程
- 討論實施可用於執行預測分析的算法的簡單五步驟過程
- 包含實際案例和範例

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