5 Architecture of an autoencoder.Figure 6 Architecture of variational autoencoder (VAE).Figure 7 Feedforward network.Figure 8 Architecture of recurrent neural network (RNN).Figure 9 Architecture of long short‐term memory network (LSTM).
3 Chapter 4Figure 1 Taxonomy of concept drift in data stream.
4 Chapter 5Figure 1 Histograms of simulated boxes and mean number of boxes for two Mont...Figure 2 Estimated risk at
5 Chapter 7Figure 1 Importance sampling with importance distribution of an exponential Figure 2 Failed simulation of a Student's
6 Chapter 9Figure 1 Graphical description of three possible dependencies between the ad...
7 Chapter 12Figure 1 Decision tree for headache data.Figure 2 RFIT analysis of the headache data: (a) Estimated ITE with SE error...Figure 3 Exploring important effect moderators in the headache data: (a) Var...Figure 4 Comparison of MSE averaged over 1000 interaction trees using method...
8 Chapter 13Figure 1 The metabolite–microbe interaction network. Only edges linking a me...Figure 2 Scatter plots of microbe and metabolite pairs.
9 Chapter 14Figure 1 An example of first‐, second‐, and third‐order tensors.Figure 2 Tensor fibers, unfolding and vectorization.Figure 3 An example of magnetic resonance imaging. The image is obtained fro...Figure 4 A third‐order tensor with a checkerbox structure.Figure 5 A schematic illustration of the low‐rank tensor clustering method....Figure 6 The tensor formulation of multidimensional advertising decisions.Figure 7 Illustration of the tensor‐based CNN compression from Kossaifi et a...
10 Chapter 15Figure 1 A Bayesian tree.Figure 2 The Boston housing data was compiled from the 1970 US Census, where...Figure 3 The distribution of
11 Chapter 16Figure 1 LASSO and nonconvex penalties: both SCAD and MCP do not penalize th...
12 Chapter 17Figure 1 Hierarchy‐preserving solution paths by RAMP. (a) Strong hierarchy; ...
13 Chapter 18Figure 1 Marginal prior of
14 Chapter 20Figure 1 ACS 2017 state estimates of the number of households (millions).Figure 2 ACS 2017 state estimates of the number of households (millions). A ...Figure 3 ACS 2017 median household income (USD) with 95% confidence interval...Figure 4 Log 10 US ACS 2017 state estimates of the number of households (per...Figure 5 ACS 2017 state estimates of the number of households (millions), wi...Figure 6 2017 ACS household median income (USD) estimates with 95% confidenc...Figure 7 Sloppy plot of 2017 ACS household median income (USD) estimates.Figure 8 Sloppy plot of 2017 ACS household median income (USD) estimates wit...Figure 9 ACS 2017 state estimates of the number of households (millions).Figure 10 ACS 2017 state estimates of the number of households (millions). T...Figure 11 2017 ACS household median income (USD) estimates with confidence i...
15 Chapter 21Figure 1 A subset of the graphical annotations used to show properties of a ...Figure 2 The process of generating a quantile dotplot from a log‐normal dist...Figure 3 Illustration of HOPs compared to error bars from the same distribut...Figure 4 Example Cone of Uncertainty produced by the National Hurricane Cent...Figure 5 (a) An example of an ensemble hurricane path display that utilizes ...
16 Chapter 22Figure 1 Classic dataflow visualization architecture.Figure 2 Client–server visualization architecture.Figure 3 (a) Piecewise linear confidence intervals and (b) bootstrapped regr...Figure 4 Dot plot and histogram.Figure 5 2D binning of 100 000 points.Figure 6 2D binning of thousands of clustered points.Figure 7 Massive data scatterplot matrix by Dan Carr [9].Figure 8 nD aggregator illustrated with 2D example.Figure 9 (a) Parallel coordinate plots of all columns and (b) aggregated