Format:
1 Online-Ressource (127 p)
Edition:
Online-Ausg.
ISBN:
9788793379312
Series Statement:
River Publishers Series in Information Science and Technology
Content:
Cover -- Half Titlle page -- River Publishers Series Page -- Title Page - Educational Data Mining with R and Rattle -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgment -- List of Figures -- List of Tables -- List of Abbreviations -- Chapter 1 - Introduction -- 1.1 Introduction -- 1.2 Data Mining -- 1.2.1 System Architecture -- 1.2.2 Mining Process -- 1.2.3 Functions and Products -- 1.2.4 Significance and Applications -- 1.3 Educational Data Mining-An Area under the Umbrella of Data Mining -- 1.3.1 EDMTasks -- 1.3.2 Techniques -- 1.4 Research Problem
Content:
1.4.1 Research Motivation -- 1.4.2 Problem Statement -- 1.4.3 Objectives -- 1.5 R Data Mining Tool -- 1.5.1 R Installation -- 1.5.2 R Mining -- 1.6 Rattle Data Mining Tool -- 1.6.1 Rattle Installation -- 1.6.2 Loading Rattle Package -- 1.7 Reason for R and Rattle -- Chapter 2 - Emerging Research Directions in Educational Data Mining -- 2.1 Introduction -- 2.2 Prior Art Vis-à-vis of Research -- 2.2.1 Educational Data Mining -- 2.2.2 Data Mining Using R -- 2.2.3 Mining Students' Academic Performance -- 2.2.4 Factors Affecting on Students' Academic Performance
Content:
2.2.5 Evaluation of Student Performance -- 2.2.6 Knowledge Management System -- 2.2.7 Placement Chance Prediction -- 2.2.8 Mining Association Rules in Student's Data -- 2.2.9 Clustering Data Mining -- 2.2.10 Prediction for Student's Performance Using Classification Method -- 2.2.11 Classification Techniques -- 2.2.12 Educational Data Mining Model Using Rattle -- 2.3 Conclusion -- Chapter 3 - Design Aspects and Developmental Framework of the System -- 3.1 Introduction -- 3.2 EDM Phases and Research Framework -- 3.3 Methods of Educational Data Mining -- 3.4 Algorithms and Tools
Content:
3.5 Data Mining Process -- 3.5.1 Data Collection -- 3.5.2 Data Preprocessing and Transformation -- 3.5.3 R Packages and Functions for Data Mining -- 3.5.4 Result Evaluation and Knowledge Presentation -- 3.6 Working with Data -- 3.7 Research Methodology -- 3.8 Loading and Exploring Data-Exploratory Data Analysis -- 3.9 Interactive Graphics and Data Visualization -- 3.10 Conclusion -- Chapter 4 - Model Development-Building Classifiers -- 4.1 Introduction-Descriptive and Predictive Analytics -- 4.2 Predictive Analytics -- 4.3 Dataset and Class Labels -- 4.4 Classification Framework and Process
Content:
4.5 Predicting Students' Performance -- 4.6 Classification and Predictive Modeling in R and Rattle -- 4.7 Decision Tree Modeling -- 4.7.1 Decision Tree Implementation in R -- 4.7.2 Decision Tree in Rattle -- 4.8 Artificial Neural Network Classifier -- 4.9 Naive Bayes Classifier -- 4.10 Random Forest Modeling -- 4.10.1 Random Forest Model in R -- 4.10.2 Random Forest Implementation in Rattle -- 4.11 Model Selection and Deployment -- 4.11.1 Model Evaluation in R -- 4.11.2 Model Evaluation in Rattle -- 4.12 Conclusion -- Chapter 5 - Educational Data Analysis: Clustering Approach -- 5.1 Introduction
Content:
5.2 Clustering in Educational Data Mining
Note:
Description based upon print version of record
Additional Edition:
9788793379305
Additional Edition:
9788793379312
Additional Edition:
Print version Kamath, R.S Educational Data Mining with R and Rattle Aalborg : River Publishers,c2016 9788793379312
Language:
English
Keywords:
Electronic books
URL:
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