Begin to Learn R
Data Analysis
Introduction R
Data Input & Output
Data Input 匯入資料
Data Output 輸出資料
Database Input 讀取資料庫
Datasets
Data Wrangling
Recode
Add a column
Factor
Grouping by date range
Reshaping Data
Reshaping: Long to Wide dcast(){reshape2}
Reshaping: Wide to Long melt(){reshape2}
Sorting Results
String Manipulation
Subset
Summaries by Subgroups {plyr}
EDA - Exploratory Data Analysis
Data Exploratory
Variable Identification
Univariate Analysis
IQR Interquartile Range
Frequency Table (Chart)
Frequency Distribution Table
Cumulative Frequency Distribution Table
Stemplot
Bi-variate Analysis
Missing values treatment
Outlier treatment
Feature Engineering
Variable transformation
Variable creation
Data Analysis
R Data Analysis
Graphical Data Analysis
Factor Analysis
PCA - Principal Components Analysis
Decision Trees
Random Forest
Clustering
Classification
SVM - Support Vector Machines
Naïve Bayes Classification
Bayesian Statistics
Bayesian Methods
Bayesian Network
Bayesian Networks Inference
Bayesian Network Applications
Time-series
R Statistics 統計
Descriptive Statistics
Mean
Mode
Median
IQR Interquartile Range
5-number summary
Variance
Standard Deviation
Standard error
Inferential statistics
Expected Value
Hypothesis Testing
T-tests
ANOVA
Chi-Square Test
Linear Regression
Linear Models
Nonlinear Regression Analysis
Logistic Regression
Generalized linear models (GLMs)
Maximum Likelihood Estimation (MLE)
Generalized Additive Models(GAM)
Survival Analysis
Distribution
Normal Distribution
Non Normal Distribution
Binomial Distribution
Poisson Distribution
Machine Learning
Unsupervised learning
Supervised learning
Reinforcement Learning
Support Vector Machine 支持向量機
Structural Change and Anomalies Detection
Crawler 網頁解析爬蟲
Binary Classification metrics
Data Communication 溝通資料
Data Visualization
Data Prediction (Modeling)
Case & Code
Application_R
Finance R
Genomics R
Clinical Research
Commerce 商業
R Basic
R Basic
Command
{base}
{stats}
Syntax
Arguments
Packages
Install & Setting
R install
R install_Ubuntu18
R setting
Environment 環境空間
Data
Data Structures
Data Frame 資料框架
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
List 列表
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
Vectors 向量 (1維)
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
Matrices 矩陣 (2維)
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
Array 陣列 (多維)
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
xts: time series data
Create/Input
Reference Elements
Modify
Operations
Output
Function
Example
Data Types
Numeric
Operations
Function
Example
Logical
Operations
Function
Example
Character 文字型別
Operations 文字操作
Create 建立
Length 量測長度
Case 大小寫
Space 空格
Output 格式化輸出
Capture 擷取
Date 日期時間
Split 分隔
Position 位置
Replace 取代
Regular Expression 正規表達
Apply to Array 應用文字處理函數至陣列
Function
Example
Factor 因子
Operations
Function
Example
Dates
Operations
Function
Example
Missing Data
Operations
Function
Example
Function
Date
Variable 變數
Discrete Variables
Continuous Variables
Quantitative Variables
Qualitative Variables
Categorical Variable
Loop
if 判斷式
switch 單選
while-loop
for-loop
repeat-loop
break loop
next loop
Graphics
Basic Graphics
Bar Chart
Histogram
Boxplot
Advanced Graphics
Package Graphics
{ggplot2} a-z
{ggplot2} option a-z
{graphics} a-z
{graphics} arguments a-z
{lattice} a-z
Save Graphs to Files
Issue 問題
Date
Time
Season
Trend
Shiny
Shiny Introduction
Build shiny applications
Learning_R
Learning Map R
R Tools
Tools
R Command A-Z
Cheat Sheet
How R
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Naïve Bayes Classification
Naïve Bayes Classification
Bayes’ theorem
is expressed by the following equation:
Reference
Classification in R Programming: The all in one tutorial to master the concept! - DataFlair
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