Features
Features:

Product Tour >

Edraw AI >

Paid Plans:

Individuals >

Business >

Eduaction >
Resources
Blog

History

How-tos & Tips

Discovery

Biography

Business Analysis

Examples

AI concept Map

Free AI Mind Map Generator

Onenote Mind Map

Bcg Matrix Examples

Nike Marketing Strategy

Unilever SWOT Analysis

Make Mind Maps in Google Docs

Guide

FAQs

What's New

Resource Center
Templates
All Templates

Brain Storming Templates

Strategy and Planning Templates

Project Management Templates

Product Management Templates

Human Resources Templates

Agile Workflow Templates

Marketing Templates

Education Templates

Fun and Games Templates

User Gallery
Download
Pricing
Enterprise

MindMap Gallery Journal of Data Science and R

Journal of Data Science and R

The role of magazine introduction is to convey the core content and characteristics of the magazine to readers, helping them quickly understand the magazine's positioning, style, and audience. At the same time, it is also an important tool to attract potential readers and showcase the magazine's brand image, which helps to enhance the magazine's visibility and influence. This is a mind map about Journal of Data Science and R. The map contains 8 main branches, namely: Introduction to Data Mining, Introduction to R, Types, Quality and Data Preprocessing, Summary Statistics and Visualization Summary, Classification and Prediction, Linear Regression with Normalization, Mining of Frequent itemsets and Association Rules Summary, Computational Methods for Big Data Analysis (Hadoop and MapReduce). Each main branch has a detailed description of its sub branches. Suitable for people interested in Journal of Data Science and R.

Edited at 2024-04-03 05:51:00

Arbayah

Recent works View more works>>

Journal of Data Science and R
The role of magazine introduction is to convey the core content and characteristics of the magazine to readers, helping them quickly understand the magazine's positioning, style, and audience. At the same time, it is also an important tool to attract potential readers and showcase the magazine's brand image, which helps to enhance the magazine's visibility and influence. This is a mind map about Journal of Data Science and R. The map contains 8 main branches, namely: Introduction to Data Mining, Introduction to R, Types, Quality and Data Preprocessing, Summary Statistics and Visualization Summary, Classification and Prediction, Linear Regression with Normalization, Mining of Frequent itemsets and Association Rules Summary, Computational Methods for Big Data Analysis (Hadoop and MapReduce). Each main branch has a detailed description of its sub branches. Suitable for people interested in Journal of Data Science and R.

Journal of Data Science and R

Arbayah

Recent works View more works>>

Journal of Data Science and R
The role of magazine introduction is to convey the core content and characteristics of the magazine to readers, helping them quickly understand the magazine's positioning, style, and audience. At the same time, it is also an important tool to attract potential readers and showcase the magazine's brand image, which helps to enhance the magazine's visibility and influence. This is a mind map about Journal of Data Science and R. The map contains 8 main branches, namely: Introduction to Data Mining, Introduction to R, Types, Quality and Data Preprocessing, Summary Statistics and Visualization Summary, Classification and Prediction, Linear Regression with Normalization, Mining of Frequent itemsets and Association Rules Summary, Computational Methods for Big Data Analysis (Hadoop and MapReduce). Each main branch has a detailed description of its sub branches. Suitable for people interested in Journal of Data Science and R.

Recommended to you
Outline

1984 - George Orwell
- 9.0k
- 59
- 5
Lisa Anderson
How to Learn Things Effectively
- 5.6k
- 82
- 8
Fiona_
Building a StoryBrand - Clarify Your Message So Customers Will Listen
- 1.6k
- 35
Second Hand Poet
EVERYTHING IS FIGUREOUTABLE
- 2.2k
- 29
- 4
Second Hand Poet
Flip the Script - Getting People to Think Your Idea is Their Idea
- 1.7k
- 22
- 1
Second Hand Poet
HOW TO BE A CAPITALIST WITHOUT ANY CAPITAL
- 480
- 6
- 3
Second Hand Poet
FREE TO FOCUS - A Total Productivity System to Achieve More by Doing Less
- 1.6k
- 67
- 14
Second Hand Poet
INDISTRACTABLE - How to Control Your Attention and Choose Your Life
- 756
- 23
- 10
Second Hand Poet
LEADERSHIFT - The 11 Essential Changes Every Leader Must Embrace
- 944
- 17
- 1
Second Hand Poet
NINE LIES ABOUT WORK - A Freethinking Leader's Guide to the Real World
- 940
- 22
- 2
Second Hand Poet

1. Introduction to Data Mining

Data Science

Knowledge Discovery in Databases (KDD)

Data Collection

Preprocessing

Transformation

Data Mining

Interpretation and Evaluation

Model Types

Examples and Counterexamples

Classification of Data Mining methods

Classification

Regression

Clustering

Extraction and Association Analysis

Visualization

Anomaly Detection

Applications

Medicine

Finance

Telecommunications

Challenges

The R Programming Language

Basic Concepts, Definitions and Notations

Tool Installation

2. : Introduction to R

Data Types

Definition and Object Classes

Vectors and Lists

Matrix

Factors and Nominal Data

Missing Values

Data Frames

Basic Tasks

Reading Data from File

Sequence creation

Reference to Subset

Vectorization

Control Structures

Conditional Statement: if-else

Loops: for, repeat and while

Next and break statements

Functions

Scoping Rules

Iterated Functions

lapply

sapply

Split

tapply

Help from the console and Package Installation

3. Types, Quality and Data Preprocessing

Categories and Types of Variables

Preprocessing processes

Data cleansing

Missing Values

Data with Noise

Inconsistent data

Data Unification

Data Transformation and Discretization

Data Transformation

Data Discretization

Data Reduction

Dimension Reduction

Data Compression

dplyr and tidyr packages

dplyr

tidyr

: Summary Statistics and Visualization summary

Measures of Position

Mean Value

Median

Measures of dispersion

Minimum value, Maximum value, Range

Percentile values

Interquartile Range

Variance

Standard Deviation

Coefficient of Variation

Visualization of Qualitative Data

Frequency Table

Bar Charts

Pie Chart

Contingency Matrix

Stacked Bar Charts and Grouped Bar Charts

Visualization of Quantitative Data

Frequency Table

Histograms

Frequency Polygon

Boxplot

Classification and Prediction

Classification

Decision Trees

Description

Decision Tree creation – ID3 Algorithm

Decision Tree creation – Gini Index

Prediction

Difference between Classification and Prediction

Linear Regression

Description, Definitions and Notations

Cost Function

Gradient Descent Algorithm

Gradient Descent in Linear Regression

Learning Parameter

Overfitting and regularization

Overfitting

Model Regularization

Linear Regression with Normalizatio

Clustering summary

Unsupervised Learning

Concept of Cluster

k-means algorithm

Algorithm Description

Random Centroids Initialization

Choosing the number of Clusters

Applying k-means in R

Hierarchical Clustering Algorithms

Distance Measurements Between Clusters

Agglomerative Algorithms

Divisive Algorithms

Applying Hierarchical Clustering in R

DBSCAN Algorithm

Basic Concepts

Algorithm Description

Algorithm Complexity

Advantages

Disadvantages

Mining of Frequent Itemsets and Association Rules summary

Introduction

Theoretical Background

Apriori Algorithm

Frequent Itemsets Types

Positive and Negative Border of Frequent Itemsets

Association Rules Mining

Alternative Methods for Large Itemsets generation

Sampling Algorithm

Partitioning Algorithm

FP-Growth Algorithm

Arules package

Computational Methods for Big Data Analysis (Hadoop and MapReduce)

Introduction

Advantages of Hadoop’s Distributed File System

Hadoop Users

Hadoop Architecture

Hadoop Distributed File System (HDFS)

HDFS Architecture

HDFS – Low Performance Areas

Low Data Access Time

Multiple Small Filesl

Multiple Data Recording Nodes, Arbitrary File Modifications

Basic HDFS Concepts

Blocks

Namenodes and Datanodes

HDFS Federation

HDFS High Availability

Data Flow – Data Reading

Network Topology in Hadoop

File Writing

Copies Placement

Consistency Model

The Hadoop Cluster Architectur

Hadoop Java API

Low Data Access Time

Generic Classes and Methods

The class Object