R: Recipes for Analysis, Visualization and Machine Learning电子书

R: Recipes for Analysis, Visualization and Machine Learning

Table of Contents

R: Recipes for Analysis, Visualization and Machine Learning

R: Recipes for Analysis, Visualization and Machine Learning

Credits

Preface

What this learning path covers

What you need for this learning path

Who this learning path is for

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Module 1

1. A Simple Guide to R

Installing packages and getting help in R

Getting ready

How to do it…

How it works…

There's more…

See also

Data types in R

How to do it…

Special values in R

How to do it…

How it works…

Matrices in R

How to do it…

How it works…

Editing a matrix in R

How to do it…

Data frames in R

How to do it…

Editing a data frame in R

How to do it...

Importing data in R

How to do it...

How it works…

Exporting data in R

How to do it…

How it works…

Writing a function in R

Getting ready

How to do it…

How it works…

See also

Writing if else statements in R

How to do it…

How it works…

Basic loops in R

How to do it…

How it works…

Nested loops in R

How to do it…

The apply, lapply, sapply, and tapply functions

How to do it…

How it works…

Using par to beautify a plot in R

How to do it…

How it works…

Saving plots

How to do it…

How it works…

2. Practical Machine Learning with R

Introduction

Downloading and installing R

Getting ready

How to do it...

How it works...

See also

Downloading and installing RStudio

Getting ready

How to do it...

How it works

See also

Installing and loading packages

Getting ready

How to do it...

How it works

See also

Reading and writing data

Getting ready

How to do it...

How it works

See also

Using R to manipulate data

Getting ready

How to do it...

How it works

There's more...

Applying basic statistics

Getting ready

How to do it...

How it works...

There's more...

Visualizing data

Getting ready

How to do it...

How it works...

See also

Getting a dataset for machine learning

Getting ready

How to do it...

How it works...

See also

3. Acquire and Prepare the Ingredients – Your Data

Introduction

Reading data from CSV files

Getting ready

How to do it...

How it works...

There's more...

Handling different column delimiters

Handling column headers/variable names

Handling missing values

Reading strings as characters and not as factors

Reading data directly from a website

Reading XML data

Getting ready

How to do it...

How it works...

There's more...

Extracting HTML table data from a web page

Extracting a single HTML table from a web page

Reading JSON data

Getting ready

How to do it...

How it works...

Reading data from fixed-width formatted files

Getting ready

How to do it...

How it works...

There's more...

Files with headers

Excluding columns from data

Reading data from R files and R libraries

Getting ready

How to do it...

How it works...

There's more...

To save all objects in a session

To selectively save objects in a session

Attaching/detaching R data files to an environment

Listing all datasets in loaded packages

Removing cases with missing values

Getting ready

How to do it...

How it works...

There's more...

Eliminating cases with NA for selected variables

Finding cases that have no missing values

Converting specific values to NA

Excluding NA values from computations

Replacing missing values with the mean

Getting ready

How to do it...

How it works...

There's more...

Imputing random values sampled from nonmissing values

Removing duplicate cases

Getting ready

How to do it...

How it works...

There's more...

Identifying duplicates (without deleting them)

Rescaling a variable to [0,1]

Getting ready

How to do it...

How it works...

There's more...

Rescaling many variables at once

See also…

Normalizing or standardizing data in a data frame

Getting ready

How to do it...

How it works...

There's more...

Standardizing several variables simultaneously

See also…

Binning numerical data

Getting ready

How to do it...

How it works...

There's more...

Creating a specified number of intervals automatically

Creating dummies for categorical variables

Getting ready

How to do it...

How it works...

There's more...

Choosing which variables to create dummies for

4. What's in There? – Exploratory Data Analysis

Introduction

Creating standard data summaries

Getting ready

How to do it...

How it works...

There's more...

Using the str() function for an overview of a data frame

Computing the summary for a single variable

Finding the mean and standard deviation

Extracting a subset of a dataset

Getting ready

How to do it...

How it works...

There's more...

Excluding columns

Selecting based on multiple values

Selecting using logical vector

Splitting a dataset

Getting ready

How to do it...

How it works...

Creating random data partitions

Getting ready

How to do it…

Case 1 – numerical target variable and two partitions

Case 2 – numerical target variable and three partitions

Case 3 – categorical target variable and two partitions

Case 4 – categorical target variable and three partitions

How it works...

There's more...

Using a convenience function for partitioning

Sampling from a set of values

Generating standard plots such as histograms, boxplots, and scatterplots

Getting ready

How to do it...

Histograms

Boxplots

Scatterplots

Scatterplot matrices

How it works...

Histograms

Boxplots

There's more...

Overlay a density plot on a histogram

Overlay a regression line on a scatterplot

Color specific points on a scatterplot

Generating multiple plots on a grid

Getting ready

How to do it...

How it works...

Graphics parameters

See also…

Selecting a graphics device

Getting ready

How to do it...

How it works...

See also…

Creating plots with the lattice package

Getting ready

How to do it...

How it works...

There's more...

Adding flair to your graphs

See also…

Creating plots with the ggplot2 package

Getting ready

How to do it...

How it works...

There's more...

Graph using qplot

Condition plots on continuous numeric variables

See also…

Creating charts that facilitate comparisons

Getting ready

How to do it...

Using base plotting system

Using ggplot2

How it works...

There's more...

Creating boxplots with ggplot2

See also…

Creating charts that help visualize a possible causality

Getting ready

How to do it...

See also…

Creating multivariate plots

Getting ready

How to do it...

How it works...

See also…

5. Where Does It Belong? – Classification

Introduction

Generating error/classification-confusion matrices

Getting ready

How to do it...

How it works...

There's more...

Visualizing the error/classification confusion matrix

Comparing the model's performance for different classes

Generating ROC charts

Getting ready

How to do it...

How it works...

There's more…

Using arbitrary class labels

Building, plotting, and evaluating – classification trees

Getting ready

How to do it...

How it works...

There's more...

Computing raw probabilities

Create the ROC Chart

See also

Using random forest models for classification

Getting ready

How to do it...

How it works...

There's more...

Computing raw probabilities

Generating the ROC chart

Specifying cutoffs for classification

See also...

Classifying using Support Vector Machine

Getting ready

How to do it...

How it works...

There's more...

Controlling scaling of variables

Determining the type of SVM model

Assigning weights to the classes

See also...

Classifying using the Naïve Bayes approach

Getting ready

How to do it...

How it works...

See also...

Classifying using the KNN approach

Getting ready

How to do it...

How it works...

There's more...

Automating the process of running KNN for many k values

Using KNN to compute raw probabilities instead of classifications

Using neural networks for classification

Getting ready

How to do it...

How it works...

There's more...

Exercising greater control over nnet

Generating raw probabilities

Classifying using linear discriminant function analysis

Getting ready

How to do it...

How it works...

There's more...

Using the formula interface for lda

See also ...

Classifying using logistic regression

Getting ready

How to do it...

How it works...

Using AdaBoost to combine classification tree models

Getting ready

How to do it...

How it works...

6. Give Me a Number – Regression

Introduction

Computing the root mean squared error

Getting ready

How to do it...

How it works...

There's more...

Using a convenience function to compute the RMS error

Building KNN models for regression

Getting ready

How to do it...

How it works...

There's more...

Running KNN with cross-validation in place of validation partition

Using a convenience function to run KNN

Using a convenience function to run KNN for multiple k values

See also...

Performing linear regression

Getting ready

How to do it...

How it works...

There's more...

Forcing lm to use a specific factor level as the reference

Using other options in the formula expression for linear models

See also...

Performing variable selection in linear regression

Getting ready

How to do it...

How it works...

See also...

Building regression trees

Getting ready

How to do it...

How it works...

There's more…

Generating regression trees for data with categorical predictors

See also...

Building random forest models for regression

Getting ready

How to do it...

How it works...

There's more...

Controlling forest generation

See also...

Using neural networks for regression

Getting ready

How to do it...

How it works...

See also...

Performing k-fold cross-validation

Getting ready

How to do it...

How it works...

See also...

Performing leave-one-out-cross-validation to limit overfitting

How to do it...

How it works...

See also...

7. Can You Simplify That? – Data Reduction Techniques

Introduction

Performing cluster analysis using K-means clustering

Getting ready

How to do it...

How it works...

There's more...

Use a convenience function to choose a value for K

See also...

Performing cluster analysis using hierarchical clustering

Getting ready

How to do it...

How it works...

See also...

Reducing dimensionality with principal component analysis

Getting ready

How to do it...

How it works...

8. Lessons from History – Time Series Analysis

Introduction

Creating and examining date objects

Getting ready

How to do it...

How it works...

See also...

Operating on date objects

Getting ready

How to do it...

How it works...

See also...

Performing preliminary analyses on time series data

Getting ready

How to do it...

How it works...

See also...

Using time series objects

Getting ready

How to do it...

How it works...

See also...

Decomposing time series

Getting ready

How to do it...

How it works...

See also...

Filtering time series data

Getting ready

How to do it...

How it works...

See also...

Smoothing and forecasting using the Holt-Winters method

Getting ready

How to do it...

How it works...

See also...

Building an automated ARIMA model

Getting ready

How to do it...

How it works...

See also...

9. It's All About Your Connections – Social Network Analysis

Introduction

Downloading social network data using public APIs

Getting ready

How to do it...

How it works...

See also...

Creating adjacency matrices and edge lists

Getting ready

How to do it...

How it works...

See also...

Plotting social network data

Getting ready

How to do it...

How it works...

There's more...

Specifying plotting preferences

Plotting directed graphs

Creating a graph object with weights

Extracting the network as an adjacency matrix from the graph object

Extracting an adjacency matrix with weights

Extracting edge list from graph object

Creating bipartite network graph

Generating projections of a bipartite network

See also...

Computing important network metrics

Getting ready

How to do it...

How it works...

There's more...

Getting edge sequences

Getting immediate and distant neighbors

Adding vertices or nodes

Adding edges

Deleting isolates from a graph

Creating subgraphs

10. Put Your Best Foot Forward – Document and Present Your Analysis

Introduction

Generating reports of your data analysis with R Markdown and knitr

Getting ready

How to do it...

How it works...

There's more...

Using the render function

Adding output options

Creating interactive web applications with shiny

Getting ready

How to do it...

How it works...

There's more...

Adding images

Adding HTML

Adding tab sets

Adding a dynamic UI

Creating single file web application

Creating PDF presentations of your analysis with R Presentation

Getting ready

How to do it...

How it works...

There's more...

Using hyperlinks

Controlling the display

Enhancing the look of the presentation

11. Work Smarter, Not Harder – Efficient and Elegant R Code

Introduction

Exploiting vectorized operations

Getting ready

How to do it...

How it works...

There's more...

Processing entire rows or columns using the apply function

Getting ready

How to do it...

How it works...

There's more...

Using apply on a three-dimensional array

Applying a function to all elements of a collection with lapply and sapply

Getting ready

How to do it...

How it works...

There's more...

Dynamic output

One caution

Applying functions to subsets of a vector

Getting ready

How to do it...

How it works...

There's more...

Applying a function on groups from a data frame

Using the split-apply-combine strategy with plyr

Getting ready

How to do it...

How it works...

There's more...

Adding a new column using transform

Using summarize along with the plyr function

Concatenating the list of data frames into a big data frame

Slicing, dicing, and combining data with data tables

Getting ready

How to do it...

How it works...

There's more...

Adding multiple aggregated columns

Counting groups

Deleting a column

Joining data tables

Using symbols

12. Where in the World? – Geospatial Analysis

Introduction

Downloading and plotting a Google map of an area

Getting ready

How to do it...

How it works...

There's more...

Saving the downloaded map as an image file

Getting a satellite image

Overlaying data on the downloaded Google map

Getting ready

How to do it...

How it works...

Importing ESRI shape files into R

Getting ready

How to do it...

How it works...

Using the sp package to plot geographic data

Getting ready

How to do it...

How it works...

Getting maps from the maps package

Getting ready

How to do it...

How it works...

Creating spatial data frames from regular data frames containing spatial and other data

Getting ready

How to do it...

How it works...

Creating spatial data frames by combining regular data frames with spatial objects

Getting ready

How to do it...

How it works...

Adding variables to an existing spatial data frame

Getting ready

How to do it...

How it works...

13. Playing Nice – Connecting to Other Systems

Introduction

Using Java objects in R

Getting ready

How to do it...

How it works...

There's more...

Checking JVM properties

Displaying available methods

Using JRI to call R functions from Java

Getting ready

How to do it...

How it works...

There's more...

Using Rserve to call R functions from Java

Getting ready

How to do it...

How it works...

There's more...

Retrieving an array from R

Executing R scripts from Java

Getting ready

How to do it...

How it works...

Using the xlsx package to connect to Excel

Getting ready

How to do it...

How it works...

Reading data from relational databases – MySQL

Getting ready

How to do it...

Using RODBC

Using RMySQL

Using RJDBC

How it works...

Using RODBC

Using RMySQL

Using RJDBC

There's more...

Fetching all rows

When the SQL query is long

Reading data from NoSQL databases – MongoDB

Getting ready

How to do it...

How it works...

There's more...

Validating your JSON

2. Module 2

1. Basic and Interactive Plots

Introduction

Introducing a scatter plot

Getting ready

How to do it…

How it works…

Scatter plots with texts, labels, and lines

How to do it…

How it works…

There's more…

See also

Connecting points in a scatter plot

How to do it…

How it works…

There's more…

See also

Generating an interactive scatter plot

Getting ready

How to do it…

How it works…

There's more…

See also

A simple bar plot

How to do it…

How it works…

There's more…

See also

An interactive bar plot

Getting ready

How to do it…

How it works…

There's more…

See also

A simple line plot

Getting ready

How to do it…

How it works…

See also

Line plot to tell an effective story

Getting ready

How to do it…

How it works…

See also

Generating an interactive Gantt/timeline chart in R

Getting ready

How to do it…

See also

Merging histograms

How to do it…

How it works…

Making an interactive bubble plot

How to do it…

How it works…

There's more…

See also

Constructing a waterfall plot in R

Getting ready

How to do it…

2. Heat Maps and Dendrograms

Introduction

Constructing a simple dendrogram

Getting ready

How to do it…

How it works…

There's more...

See also

Creating dendrograms with colors and labels

Getting ready

How to do it…

How it works…

There's more…

Creating a heat map

Getting ready

How to do it…

How it works…

There's more…

See also

Generating a heat map with customized colors

Getting ready

How to do it…

How it works…

Generating an integrated dendrogram and a heat map

How to do it…

There's more…

See also

Creating a three-dimensional heat map and a stereo map

Getting ready

How to do it…

See also

Constructing a tree map in R

Getting ready

How to do it…

How it works…

There's more…

See also

3. Maps

Introduction

Introducing regional maps

Getting ready

How to do it…

How it works…

See also

Introducing choropleth maps

Getting ready

How to do it…

How it works…

There's more…

See also

A guide to contour maps

How to do it…

How it works…

There's more…

See also

Constructing maps with bubbles

Getting ready

How to do it…

How it works...

There's more…

See also

Integrating text with maps

Getting ready

How to do it…

See also

Introducing shapefiles

Getting ready

How to do it…

See also

Creating cartograms

Getting ready

How to do it…

See also

4. The Pie Chart and Its Alternatives

Introduction

Generating a simple pie chart

How to do it…

How it works…

There's more...

See also

Constructing pie charts with labels

Getting ready

How to do it…

How it works…

There's more…

Creating donut plots and interactive plots

Getting rady

How to do it...

How it works…

There's more…

See also

Generating a slope chart

Getting ready

How to do it…

How it works…

See also

Constructing a fan plot

Getting ready

How to do it…

How it works…

5. Adding the Third Dimension

Introduction

Constructing a 3D scatter plot

Getting ready

How to do it…

How it works…

There's more…

See also

Generating a 3D scatter plot with text

Getting ready

How to do it…

How it works…

There's more…

See also

A simple 3D pie chart

Getting ready

How to do it…

How it works…

A simple 3D histogram

Getting ready

How to do it…

How it works…

There's more...

Generating a 3D contour plot

Getting ready

How to do it…

How it works…

Integrating a 3D contour and a surface plot

Getting ready

How to do it…

How it works…

There's more...

See also

Animating a 3D surface plot

Getting ready

How to do it…

How it works…

There's more…

See also

6. Data in Higher Dimensions

Introduction

Constructing a sunflower plot

Getting ready

How to do it…

How it works…

See also

Creating a hexbin plot

Getting ready

How to do it…

How it works…

See also

Generating interactive calendar maps

Getting ready

How to do it…

How it works…

See also

Creating Chernoff faces in R

Getting ready

How to do it…

How it works…

Constructing a coxcomb plot in R

Getting ready

How to do it…

How it works…

See also

Constructing network plots

Getting ready

How to do it…

How it works…

There's more…

See also

Constructing a radial plot

Getting ready

How to do it…

How it works…

There's more…

See also

Generating a very basic pyramid plot

Getting ready

How to do it…

How it works…

See also

7. Visualizing Continuous Data

Introduction

Generating a candlestick plot

Getting ready

How to do it…

How it works…

There's more…

See also

Generating interactive candlestick plots

Getting ready

How to do it…

How it works…

Generating a decomposed time series

How to do it…

How it works…

There's more…

See also

Plotting a regression line

How to do it…

How it works…

See also

Constructing a box and whiskers plot

Getting ready

How to do it…

How it works…

See also

Generating a violin plot

Getting ready

How to do it…

Generating a quantile-quantile plot (QQ plot)

Getting ready

How to do it…

See also

Generating a density plot

Getting ready

How to do it…

How it works…

There's more…

See also

Generating a simple correlation plot

Getting ready

How to do it…

How it works…

There's more…

See also

8. Visualizing Text and XKCD-style Plots

Introduction

Generating a word cloud

Getting ready

How to do it…

How it works…

There's more…

See also

Constructing a word cloud from a document

Getting ready

How to do it…

How it works…

There's more…

See also

Generating a comparison cloud

Getting ready

How to do it…

How it works…

See also

Constructing a correlation plot and a phrase tree

Getting ready

How to do it…

How it works…

There's more…

See also

Generating plots with custom fonts

Getting ready

How to do it…

How it works…

See also

Generating an XKCD-style plot

Getting ready

How to do it…

See also

9. Creating Applications in R

Introduction

Creating animated plots in R

Getting ready

How to do it…

How it works…

Creating a presentation in R

Getting ready

How to do it…

How it works…

There's more…

See also

A basic introduction to API and XML

Getting ready

How to do it…

How it works…

See also

Constructing a bar plot using XML in R

Getting ready

How to do it…

How it works…

See also

Creating a very simple shiny app in R

Getting ready

How to do it…

How it works…

See also

3. Module 3

1. Data Exploration with RMS Titanic

Introduction

Reading a Titanic dataset from a CSV file

Getting ready

How to do it...

How it works...

There's more...

Converting types on character variables

Getting ready

How to do it...

How it works...

There's more...

Detecting missing values

Getting ready

How to do it...

How it works...

There's more...

Imputing missing values

Getting ready

How to do it...

How it works...

There's more...

Exploring and visualizing data

Getting ready

How to do it...

How it works...

There's more...

See also

Predicting passenger survival with a decision tree

Getting ready

How to do it...

How it works...

There's more...

Validating the power of prediction with a confusion matrix

Getting ready

How to do it...

How it works...

There's more...

Assessing performance with the ROC curve

Getting ready

How to do it...

How it works...

See also

2. R and Statistics

Introduction

Understanding data sampling in R

Getting ready

How to do it...

How it works...

See also

Operating a probability distribution in R

Getting ready

How to do it...

How it works...

There's more...

Working with univariate descriptive statistics in R

Getting ready

How to do it...

How it works...

There's more...

Performing correlations and multivariate analysis

Getting ready

How to do it...

How it works...

See also

Operating linear regression and multivariate analysis

Getting ready

How to do it...

How it works...

See also

Conducting an exact binomial test

Getting ready

How to do it...

How it works...

See also

Performing student's t-test

Getting ready

How to do it...

How it works...

See also

Performing the Kolmogorov-Smirnov test

Getting ready

How to do it...

How it works...

See also

Understanding the Wilcoxon Rank Sum and Signed Rank test

Getting ready

How to do it...

How it works...

See also

Working with Pearson's Chi-squared test

Getting ready

How to do it

How it works...

There's more...

Conducting a one-way ANOVA

Getting ready

How to do it...

How it works...

There's more...

Performing a two-way ANOVA

Getting ready

How to do it...

How it works...

See also

3. Understanding Regression Analysis

Introduction

Fitting a linear regression model with lm

Getting ready

How to do it...

How it works...

There's more...

Summarizing linear model fits

Getting ready

How to do it...

How it works...

See also

Using linear regression to predict unknown values

Getting ready

How to do it...

How it works...

See also

Generating a diagnostic plot of a fitted model

Getting ready

How to do it...

How it works...

There's more...

Fitting a polynomial regression model with lm

Getting ready

How to do it...

How it works

There's more...

Fitting a robust linear regression model with rlm

Getting ready

How to do it...

How it works

There's more...

Studying a case of linear regression on SLID data

Getting ready

How to do it...

How it works...

See also

Applying the Gaussian model for generalized linear regression

Getting ready

How to do it...

How it works...

See also

Applying the Poisson model for generalized linear regression

Getting ready

How to do it...

How it works...

See also

Applying the Binomial model for generalized linear regression

Getting ready

How to do it...

How it works...

See also

Fitting a generalized additive model to data

Getting ready

How to do it...

How it works

See also

Visualizing a generalized additive model

Getting ready

How to do it...

How it works...

There's more...

Diagnosing a generalized additive model

Getting ready

How to do it...

How it works...

There's more...

4. Classification (I) – Tree, Lazy, and Probabilistic

Introduction

Preparing the training and testing datasets

Getting ready

How to do it...

How it works...

There's more...

Building a classification model with recursive partitioning trees

Getting ready

How to do it...

How it works...

See also

Visualizing a recursive partitioning tree

Getting ready

How to do it...

How it works...

See also

Measuring the prediction performance of a recursive partitioning tree

Getting ready

How to do it...

How it works...

See also

Pruning a recursive partitioning tree

Getting ready

How to do it...

How it works...

See also

Building a classification model with a conditional inference tree

Getting ready

How to do it...

How it works...

See also

Visualizing a conditional inference tree

Getting ready

How to do it...

How it works...

See also

Measuring the prediction performance of a conditional inference tree

Getting ready

How to do it...

How it works...

See also

Classifying data with the k-nearest neighbor classifier

Getting ready

How to do it...

How it works...

See also

Classifying data with logistic regression

Getting ready

How to do it...

How it works...

See also

Classifying data with the Naïve Bayes classifier

Getting ready

How to do it...

How it works...

See also

5. Classification (II) – Neural Network and SVM

Introduction

Classifying data with a support vector machine

Getting ready

How to do it...

How it works...

See also

Choosing the cost of a support vector machine

Getting ready

How to do it...

How it works...

See also

Visualizing an SVM fit

Getting ready

How to do it...

How it works...

See also

Predicting labels based on a model trained by a support vector machine

Getting ready

How to do it...

How it works...

There's more...

Tuning a support vector machine

Getting ready

How to do it...

How it works...

See also

Training a neural network with neuralnet

Getting ready

How to do it...

How it works...

See also

Visualizing a neural network trained by neuralnet

Getting ready

How to do it...

How it works...

See also

Predicting labels based on a model trained by neuralnet

Getting ready

How to do it...

How it works...

See also

Training a neural network with nnet

Getting ready

How to do it...

How it works...

See also

Predicting labels based on a model trained by nnet

Getting ready

How to do it...

How it works...

See also

6. Model Evaluation

Introduction

Estimating model performance with k-fold cross-validation

Getting ready

How to do it...

How it works...

There's more...

Performing cross-validation with the e1071 package

Getting ready

How to do it...

How it works...

See also

Performing cross-validation with the caret package

Getting ready

How to do it...

How it works...

See also

Ranking the variable importance with the caret package

Getting ready

How to do it...

How it works...

There's more...

Ranking the variable importance with the rminer package

Getting ready

How to do it...

How it works...

See also

Finding highly correlated features with the caret package

Getting ready

How to do it...

How it works...

See also

Selecting features using the caret package

Getting ready

How to do it...

How it works...

See also

Measuring the performance of the regression model

Getting ready

How to do it...

How it works...

There's more…

Measuring prediction performance with a confusion matrix

Getting ready

How to do it...

How it works...

See also

Measuring prediction performance using ROCR

Getting ready

How to do it...

How it works...

See also

Comparing an ROC curve using the caret package

Getting ready

How to do it...

How it works...

See also

Measuring performance differences between models with the caret package

Getting ready

How to do it...

How it works...

See also

7. Ensemble Learning

Introduction

Classifying data with the bagging method

Getting ready

How to do it...

How it works...

There's more...

Performing cross-validation with the bagging method

Getting ready

How to do it...

How it works...

See also

Classifying data with the boosting method

Getting ready

How to do it...

How it works...

There's more...

Performing cross-validation with the boosting method

Getting ready

How to do it...

How it works...

See also

Classifying data with gradient boosting

Getting ready

How to do it...

How it works...

There's more...

Calculating the margins of a classifier

Getting ready

How to do it...

How it works...

See also

Calculating the error evolution of the ensemble method

Getting ready

How to do it...

How it works...

See also

Classifying data with random forest

Getting ready

How to do it...

How it works...

There's more...

Estimating the prediction errors of different classifiers

Getting ready

How to do it...

How it works...

See also

8. Clustering

Introduction

Clustering data with hierarchical clustering

Getting ready

How to do it...

How it works...

There's more...

Cutting trees into clusters

Getting ready

How to do it...

How it works...

There's more...

Clustering data with the k-means method

Getting ready

How to do it...

How it works...

See also

Drawing a bivariate cluster plot

Getting ready

How to do it...

How it works...

There's more

Comparing clustering methods

Getting ready

How to do it...

How it works...

See also

Extracting silhouette information from clustering

Getting ready

How to do it...

How it works...

See also

Obtaining the optimum number of clusters for k-means

Getting ready

How to do it...

How it works...

See also

Clustering data with the density-based method

Getting ready

How to do it...

How it works...

See also

Clustering data with the model-based method

Getting ready

How to do it...

How it works...

See also

Visualizing a dissimilarity matrix

Getting ready

How to do it...

How it works...

There's more...

Validating clusters externally

Getting ready

How to do it...

How it works...

See also

9. Association Analysis and Sequence Mining

Introduction

Transforming data into transactions

Getting ready

How to do it...

How it works...

See also

Displaying transactions and associations

Getting ready

How to do it...

How it works...

See also

Mining associations with the Apriori rule

Getting ready

How to do it...

How it works...

See also

Pruning redundant rules

Getting ready

How to do it...

How it works...

See also

Visualizing association rules

Getting ready

How to do it...

How it works...

See also

Mining frequent itemsets with Eclat

Getting ready

How to do it...

How it works...

See also

Creating transactions with temporal information

Getting ready

How to do it...

How it works...

See also

Mining frequent sequential patterns with cSPADE

Getting ready

How to do it...

How it works...

See also

10. Dimension Reduction

Introduction

Performing feature selection with FSelector

Getting ready

How to do it...

How it works...

See also

Performing dimension reduction with PCA

Getting ready

How to do it...

How it works...

There's more...

Determining the number of principal components using the scree test

Getting ready

How to do it...

How it works...

There's more...

Determining the number of principal components using the Kaiser method

Getting ready

How to do it...

How it works...

See also

Visualizing multivariate data using biplot

Getting ready

How to do it...

How it works...

There's more...

Performing dimension reduction with MDS

Getting ready

How to do it...

How it works...

There's more...

Reducing dimensions with SVD

Getting ready

How to do it...

How it works...

See also

Compressing images with SVD

Getting ready

How to do it...

How it works...

See also

Performing nonlinear dimension reduction with ISOMAP

Getting ready

How to do it...

How it works...

There's more...

Performing nonlinear dimension reduction with Local Linear Embedding

Getting ready

How to do it...

How it works...

See also

11. Big Data Analysis (R and Hadoop)

Introduction

Preparing the RHadoop environment

Getting ready

How to do it...

How it works...

See also

Installing rmr2

Getting ready

How to do it...

How it works...

See also

Installing rhdfs

Getting ready

How to do it...

How it works...

See also

Operating HDFS with rhdfs

Getting ready

How to do it...

How it works...

See also

Implementing a word count problem with RHadoop

Getting ready

How to do it...

How it works...

See also

Comparing the performance between an R MapReduce program and a standard R program

Getting ready

How to do it...

How it works...

See also

Testing and debugging the rmr2 program

Getting ready

How to do it...

How it works...

See also

Installing plyrmr

Getting ready

How to do it...

How it works...

See also

Manipulating data with plyrmr

Getting ready

How to do it...

How it works...

See also

Conducting machine learning with RHadoop

Getting ready

How to do it...

How it works...

See also

Configuring RHadoop clusters on Amazon EMR

Getting ready

How to do it...

How it works...

See also

A. Resources for R and Machine Learning

B. Dataset – Survival of Passengers on the Titanic

A. Bibliography

Index