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Getting ready
by Chiu Yu-Wei, AshishSingh Bhatia
Machine Learning with R Cookbook - Second Edition
Preface
What this book covers
What you need for this book
Who this book is for
Sections
Getting ready
How to do it…
How it works…
There's more…
See also
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
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
Understanding of basic data structures
Data types
Data structures
Vectors
How to do it...
How it works...
Lists
How to do it...
How it works...
Array
How to do it...
How it works...
Matrix
How to do it...
DataFrame
How to do it...
Basic commands for subsetting
How to do it...
Data input
Reading and writing data
Getting ready
How to do it...
How it works...
There's more...
Manipulating 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
Data Exploration with Air Quality Datasets
Introduction
Using air quality dataset
Getting ready
How to do it...
How it works...
There's more...
Converting attributes to factor
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...
Exploring and visualizing data
Getting ready
How to do it...
Predicting values from datasets
Getting ready
How to do it...
How it works...
Analyzing Time Series Data
Introduction
Looking at time series data
Getting ready
How to do it...
How it works...
See also
Plotting and forecasting time series data
Getting ready
How to do it...
How it works...
See also
Extracting, subsetting, merging, filling, and padding
Getting ready
How to do it...
How it works...
See also
Successive differences and moving averages
Getting ready
How to do it...
How it works...
See also
Exponential smoothing
Getting ready
How to do it...
How it works...
See also
Plotting the autocorrelation function
Getting ready
How to do it...
How it works...
See also
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
Conducting an exact binomial test
Getting ready
How to do it...
How it works...
See also
Performing a 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
Understanding Regression Analysis
Introduction
Different types of regression
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 multiple regression
Getting ready
How to do it...
How it works...
Summarizing multiple regression
Getting ready
How to do it...
How it works...
See also
Using multiple regression to predict unknown values
Getting ready
How to do it...
How it works...
See also
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...
Survival Analysis
Introduction
Loading and observing data
Getting ready
How to do it...
How it works...
There's more...
Viewing the summary of survival analysis
Getting ready
How to do it...
How it works...
Visualizing the Survival Curve
Getting ready
How to do it...
How it works...
Using the log-rank test
Getting ready
How to do it...
How it works...
Using the COX proportional hazard model
Getting ready
How to do it...
How it works...
Nelson-Aalen Estimator of cumulative hazard
Getting ready
How to do it...
How it works...
See also
Classification 1 - 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
Handling missing data and split and surrogate variables
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
Control parameters in conditional inference trees
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
Classification 2 - 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
The basics of neural network
Getting ready
How to do it...
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
Model Evaluation
Introduction
Why do models need to be evaluated?
Different methods of model evaluation
Estimating model performance with k-fold cross-validation
Getting ready
How to do it...
How it works...
There's more...
Estimating model performance with Leave One Out Cross Validation
Getting ready
How to do it...
How it works...
See also
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
Ensemble Learning
Introduction
Using the Super Learner algorithm
Getting ready
How to do it...
How it works...
Using ensemble to train and test
Getting ready
How to do it...
How it works...
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
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
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
Using the TraMineR package for sequence analysis
Getting ready
How to do it...
How it works...
Visualizing sequence, Chronogram, and Traversal Statistics
Getting ready
How to do it...
How it works...
See also
Dimension Reduction
Introduction
Why to reduce the dimension?
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
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
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