Index
A
- aggregation operations
- about / Aggregation operations on the data
- mean / Mean
- median / Median
- sum / Sum
- minimum / Maximum and minimum
- maximum / Maximum and minimum
- standard deviation / Standard deviation
- Apriori analysis
- about / Apriori analysis
- Apriori sequence analysis
- about / Apriori sequence analysis
- reference link / Apriori sequence analysis
- business cases / Business cases
- arithmetic operations
- association rule analysis, parameters
- support / Support, confidence, and lift, Support
- confidence / Support, confidence, and lift, Confidence
- lift / Support, confidence, and lift, Lift
- autoregressive integrated moving average (ARIMA)
- used, for forecasting / Forecasting using ARIMA
- order parameter / Forecasting using ARIMA
- order parameter, URL / Forecasting using ARIMA
B
- bivariate analysis
- about / Bivariate analysis
- box plot
- plotting, for descriptive statistics / Box plot
- break control structure
C
- Cassandra
- about / Reading data from a database
- centroid-based clustering
- clustering
- datasets, using / Datasets
- datasets, reading / Reading and formatting the dataset in R
- datasets, formatting / Reading and formatting the dataset in R
- business use cases / Business use cases
- clusters
- ideal number, obtaining / Centroid-based clustering and an ideal number of clusters
- implementing, K-means algorithm used / Implementation using K-means
- visualizing / Visualizing the clusters
- comma-separated values (CSV) format
- connectivity-based clustering
- about / Connectivity-based clustering
- visualizing / Visualizing the connectivity
- control structures
- about / Control structures in R
- if and else / Control structures – if and else
- for / Control structures – for
- while / Control structures – while
- repeat / Control structures – repeat and break
- break / Control structures – repeat and break
- next / Control structures – next and return
- return / Control structures – next and return
- cross tabulation analysis
- about / Cross-tabulation analysis
D
- data
- reading, from different source / Reading data from different sources
- reading, from database / Reading data from a database
- preparing, for analysis / Bringing data to a usable format
- dataframe
- about / Variable data types
- data operations
- performing / Performing data operations
- arithmetic operations / Arithmetic operations on the data
- string operations / String operations on the data
- aggregation operations / Aggregation operations on the data
- data preprocessing
- techniques / Data preprocessing techniques
- dataset
- data types
- about / Data types in R
- variable data types / Variable data types
- vector / Variable data types
- matrix / Variable data types
- list / Variable data types
- factors / Variable data types
- dataframe / Variable data types
- data visualization
- dataset, using / Dataset
- plotting, googleVis package used / Plotting using the googleVis package
- interactive dashboard, creating with Shiny / Creating an interactive dashboard using Shiny
- DBI driver
- about / Reading data from a database
- descriptive statistics
- about / Descriptive statistics
- box plot / Box plot
E
- ensemble models
- building / Ensemble models
- NA values, replacing with mean or median / Replacing NA with mean or median
- highly correlated values, removing / Removing the highly correlated values
- outliers, removing / Removing outliers
F
- factors
- about / Variable data types
- forecasting
- datasets, using / Datasets
- extracting patterns / Extracting patterns
- autoregressive integrated moving average (ARIMA), using / Forecasting using ARIMA
- Holt-Winters, using / Forecasting using Holt-Winters
- accuracy, improving / Methods to improve accuracy
- for loop
- about / Control structures – for
G
- googleVis package
- used, for plotting data visualization / Plotting using the googleVis package
- reference link / Plotting using the googleVis package
- graphical analysis
- about / Graphical analysis
H
- Hadoop
- about / Reading data from a database
- Holt-Winters
- used, for forecasting / Forecasting using Holt-Winters
- URL / Forecasting using Holt-Winters
I
- if and else control structure
- about / Control structures – if and else
- in-built dataset
- using / Using the built-in dataset
- inferential statistics
- about / Inferential statistics
- interactive dashboard
- creating, Shiny used / Creating an interactive dashboard using Shiny
- item-based CF method
- used, for implementing recommendation system / Recommendations using item-based CF
J
- JDBC driver
K
- K-means algorithm
- using / Centroid-based clustering and an ideal number of clusters
- used, for cluster implementation / Implementation using K-means
L
- linear regression
- about / Linear regression
- evaluating / Evaluating linear regression
- list
- about / Variable data types
- logistic regression
- about / Logistic regression
- evaluating / Evaluating logistic regression
M
- matrix
- about / Variable data types
- MongoDB
- about / Reading data from a database
- multivariate analysis
- about / Multivariate analysis
- cross tabulation analysis / Cross-tabulation analysis
- graphical analysis / Graphical analysis
N
- next control structure
O
- Oracle
- about / Reading data from a database
P
- PostgreSQL
- about / Reading data from a database
- public dataset
- references / Exercise
R
- Random Forest
- about / Ensemble models
- recommendation system
- dataset, using / Dataset and transformation
- implementing, user-based CF method used / Recommendations using user-based CF
- implementing, item-based CF method used / Recommendations using item-based CF
- challenges / Challenges and enhancements
- enhancements / Challenges and enhancements
- regression models
- datasets, using / Datasets
- dataset, sampling / Sampling the dataset
- logistic regression / Logistic regression
- linear regression / Linear regression
- accuracy, improving / Methods to improve the accuracy
- ensemble models, building / Ensemble models
- Support Vector Machine (SVM) / Ensemble models
- Random Forest / Ensemble models
- repeat control structure
- return control structure
- rules
- filtering / Generating filtering rules
- plotting / Rules
- results, checking / Understanding the results
- references / Reference
S
- SAS
- about / Reading data from a database
- Seasonal Decomposition of Time series
- about / Extracting patterns
- sensitivity and specificity
- reference link / Evaluating logistic regression
- sequential dataset
- about / Sequential dataset
- Shiny
- about / Creating an interactive dashboard using Shiny
- used, for creating interactive dashboard / Creating an interactive dashboard using Shiny
- reference link / Creating an interactive dashboard using Shiny
- SPSS
- about / Reading data from a database
- SQL Server
- about / Reading data from a database
- Stata
- about / Reading data from a database
- stl function
- about / Extracting patterns
- reference link / Extracting patterns
- string operations
- about / String operations on the data
- Support Vector Machine (SVM)
- about / Ensemble models
- Systat
- about / Reading data from a database
T
- Titanic dataset
- using / The Titanic dataset
- URL / The Titanic dataset
- variables / The Titanic dataset
- transactional datasets
- about / Transactional datasets
- in-built dataset, using / Using the built-in dataset
- building / Building the dataset
U
- univariate analysis
- about / Univariate analysis
- user-based CF method
- used, for implementing recommendation system / Recommendations using user-based CF
V
- variable data types
- about / Variable data types
- vector
- about / Variable data types
W
- while loop
- about / Control structures – while