I'm trying to use the data visualization feature in catboost - the one that visualizes training vs validation error (learning curve):
model.fit(X_train, y_train,cat_features=categorical_features_indices,eval_set=(X_val, y_val),verbose=False,plot=True)
I defined in fit method plot = True but no plot has shown up.
I also tried running the Catboost documentation example: https://catboost.ai/docs/features/visualization_jupyter-notebook.html#visualization_jupyter-notebook but it doesn't work either.
I'm using Jupyter notebook in Chrome.
Related
Im' trying to replicate the top 3D scatter plot on this website,
Unfortunately, this website doesn't contain any code, and doesn't specify clearly which package is used, and a google search yielded no useful results. I would like to replicate this plot with my own data, and get it in a format that's useful in a publication. Any suggestions?
I want to export the plot points of a cox regression survival plot so i can use it in Graphpad Prism to make a nice graph out of it.
Question
How can i export the plot points?
is there maybe an easier way to export such a graph to edit it in graphpad?
You should add a save subcommand to your analysis syntax:
/SAVE=SURVIVAL
After running the analysis you will find new column(s) containing the survival data which you can then export and plot elsewhere.
If you look in the Menu for the analysis you can see a button called - click it to see all options of new variables to save, maybe you can find other data useful.
tl;dr
What is the R code that takes the keras history form and produces not the tensorflow/keras plot shown below but the ggplot shown slightly farther below?
Details:
Rstudio has a wrapper for keras:
https://tensorflow.rstudio.com/guide/keras/
When training a model, it displays a plot of the loss and metrics over time. I think it is using plotly. I am not interested in the graph that has these stylings.
You can take the history object an plot it again, and it generates a new plot. If you have 'ggplot2' installed, then it uses ggplot.
I am looking for something like this, the product of ggplot2:
What is the R code that takes the keras history form and produces that ggplot?
I am not looking for the wrapper which is 'plot(history)', but the set of frame manipulations and input commands to ggplot that generate the output. It should contain something of the form'ggplot(history, aes(...)) + ...'
After keras fit is called, although with interactive metrics turned off by argument, I can not output plots to knitr generated HTML anymore.
I've tried dev.off() after keras fit call with and without plot.new(), as well as various combinations of dev.flush(), dev.new() etc.
I want calls to ggplot() produce plots, but instead I get errors such as replayPlot(x): invalid graphics state without running dev.off() after keras fit, and just no plot rendered in html output if I run dev.off() & plot.new().
I am new to R and I am trying to build a decision tree using rpart.
However when I plotted the model using plot(fit) where fit = model, the output displayed was all lines and no texts/ no variable names. Is there anything that must be wrong with my settings?