Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar jectives Data Mining Cours Goals and Objectives of Data Mining Classification Techniques Association Analysis Clustering Algorithms Exploratory Data Analysi and Preprocessing Apply Data Mining to Real World Datasets Learn How to Interpret Data Mining Results Implementing Data Mining Algorithms Using R for Data Analysis and Data Mining Making Sense of Data
Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar
Feb 08, 2016
Objectives Data Mining Course. Lecture Notes for Chapter 4 Introduction to Data Mining by Tan, Steinbach, Kumar. Using R for Data Analysis and Data Mining. Apply Data Mining to Real World Datasets. Exploratory Data Analysis and Preprocessing. - PowerPoint PPT Presentation
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Lecture Notes for Chapter 4
Introduction to Data Miningby
Tan, Steinbach, Kumar
Objectives Data Mining Course
Goals and Objectives of Data Mining
Classification Techniques
Association Analysis
Clustering Algorithms
Exploratory Data Analysisand Preprocessing
Apply Data Mining to Real World Datasets
Learn How to InterpretData Mining Results
Implementing Data Mining Algorithms
Using R forData Analysis
and Data Mining
Making Sense of Data
Top 10 Data Mining Algorithms
SVMK-means
PageRank
C4.5
APRIORIEM
CART
AdaBoostkNN
Naïve Bayes
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