PDPbox | python partial dependence plot toolbox | Code Editor library

by SauceCat Jupyter Notebook Version: 0.3.0 License: MIT

X-Ray Key Features Code Snippets(1)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | PDPbox Summary

PDPbox is a Jupyter Notebook library typically used in Editor, Code Editor applications. PDPbox has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

python partial dependence plot toolbox.

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PDPbox has a low active ecosystem.

It has 747 star(s) with 124 fork(s). There are 17 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 23 open issues and 39 have been closed. On average issues are closed in 543 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of PDPbox is 0.3.0

Quality

PDPbox has 0 bugs and 0 code smells.

Security

PDPbox has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

PDPbox code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PDPbox is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

PDPbox releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 6604 lines of code, 285 functions and 29 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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PDPbox Key Features

No Key Features are available at this moment for PDPbox.

PDPbox Examples and Code Snippets

Partial dependence plot (PDPbox) error on lightGBM model: "wrong number of items passed 3, placement implies "

Python

Lines of Code : 27

License : Strong Copyleft (CC BY-SA 4.0)

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import lightgbm as lgb
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from pdpbox import pdp, get_dataset, info_plots

#load some data
df = sns.load_dataset("iris")
X =

Community Discussions

Trending Discussions on PDPbox

python pdpbox plot with unscaled feature values

QUESTION

python pdpbox plot with unscaled feature values

Asked 2020-Sep-04 at 05:35

I'm trying to plot the Partial Dependence and ICE plots for a Multi-layer perceptron classifier. I'm using the UCI Adult dataset. I have Label Encoded the categorical features and Scaled the overall dataframe and then performed a test-train split on the scaled dataframe.

Now when I'm trying to plot the PDP and ICE plots I get the Age values (column in the X Axis of the plot) as scaled and hence not comprehend-able. I want the age values to be the original values before scaling was performed on the data. How can I achieve this?

This is the code for the plots:

...

ANSWER

Answered 2020-Sep-04 at 05:35

I was able to solve the above problem by using a Pipeline object. I used one hot encoding for the categorical variables and then pushed the scaling and the classifier operations into the Pipeline object. I was then able to use the encoded X_train without any issues for the partial dependence plot and I got the actual Age value ranges, what I was looking for.

Source https://stackoverflow.com/questions/63720200

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install PDPbox

through pip (latest stable version： 0.2.1). through git (latest develop version).
through pip (latest stable version： 0.2.1) $ pip install pdpbox
through git (latest develop version) $ git clone https://github.com/SauceCat/PDPbox.git $ cd PDPbox $ python setup.py install