Description Usage Arguments Value
plot_dlayer Visualize hidden layer activations in a deep learning model with dimentionality reduction and variable labels
1 2 | plot_dlayer(model, vis_data, layer, label, dimentions = 2,
max_points = 1000, tsne_iter = 500, wd = getwd())
|
model |
H2O model object containing labeled data for model training. No Default. |
vis_data |
H2O frame object containing data to caculate layer activations. No Default. |
layer |
Numeric object of length 1 identifying the which hidden layer to visualize. No Defalut. |
label |
Character object of length 1 identifying the column name of the variable in vis_data to label visulaizaion points with. No Default. |
dimentions |
Numeric object set to 2 or 3, 2 returns ggplot figure, 3 returns plotly html page |
max_points |
Numeric object setting maximum number of observations in visualization. A number of rows equal to max_points from vis_data are sampled with out replacement for the visulaization. |
tsne_iter |
Numberic object sets the number of iterations in t-tailed stochastic nearest neighbors dimentionality reduction operation. Defaults to 1000. |
wd |
Character object defining file path where html interactive graphic will be saved if dimentions = 3. Defaults to current working directory. |
None
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