scikit-plot | intuitive library to add plotting functionality | Machine Learning library

by reiinakano Python Version: 0.3.7 License: MIT

X-Ray Key Features Code Snippets(8)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | scikit-plot Summary

scikit-plot is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Pandas applications. scikit-plot has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can install using 'pip install scikit-plot' or download it from GitHub, PyPI.

An intuitive library to add plotting functionality to scikit-learn objects.

Support

Quality

Security

License

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Support

scikit-plot has a highly active ecosystem.

It has 2290 star(s) with 279 fork(s). There are 65 watchers for this library.

It had no major release in the last 12 months.

There are 19 open issues and 39 have been closed. On average issues are closed in 56 days. There are 6 open pull requests and 0 closed requests.

It has a positive sentiment in the developer community.

The latest version of scikit-plot is 0.3.7

Quality

scikit-plot has 0 bugs and 127 code smells.

Security

scikit-plot has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

scikit-plot code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

scikit-plot 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

scikit-plot releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

scikit-plot saves you 1369 person hours of effort in developing the same functionality from scratch.

It has 3065 lines of code, 275 functions and 32 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed scikit-plot and discovered the below as its top functions. This is intended to give you an instant insight into scikit-plot implemented functionality, and help decide if they suit your requirements.

Plot confusion matrix
Validate that the passed_labels argument is valid
Plot the KS statistic
Calculates the k - statistic for the classification statistic
Read data from multiple files

Get all kandi verified functions for this library.

scikit-plot Key Features

No Key Features are available at this moment for scikit-plot.

scikit-plot Examples and Code Snippets

Google Cloud Function: FunctionsError: OperationError: code=13, message=Function deployment failed due to a health check failure

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

Copy

werkzeug==0.14.1

werkzeug

Confusion matrix predicted labels

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

skplt.metrics.plot_confusion_matrix(y_test, y_pred, x_tick_rotation=45, normalize=True)

How to build a lift chart (a.k.a gains chart) in Python?

Python

Lines of Code : 20

License : Strong Copyleft (CC BY-SA 4.0)

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skplt.metrics.plot_cumulative_gain(y_test, predicted_probas)

# The usual train-test split mumbo-jumbo
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklear

Plot only Class 1 vs Baseline in Lift-curve and Cumulative-gains-chart in scikitplot

Python

Lines of Code : 25

License : Strong Copyleft (CC BY-SA 4.0)

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def get_cum_gains(df, score, target, title):
    df1 = df[[score,target]].dropna()
    fpr, tpr, thresholds = roc_curve(df1[target], df1[score])
    ppr=(tpr*df[target].sum()+fpr*(df[target].count()- 
    df[target].sum()))/df[target].coun

Plotting confusion matrix

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

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pip uninstall matplotlib
pip install matplotlib=='3.0.3'

Change default line width in scikitplot

Python

Lines of Code : 8

License : Strong Copyleft (CC BY-SA 4.0)

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lr = LogisticRegression()
lr = lr.fit(X_train, y_train)
y_probas = lr.predict_proba(X_test)
ax = skplt.metrics.plot_lift_curve(y_test, y_probas)
for l in ax.lines:
    l.set_lw(0.5)
plt.show()

How to merge the plots of 2 lift curves into a single graph in Python

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

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ax = skplt.metrics.plot_lift_curve(y_test, log_y_probas)
skplt.metrics.plot_lift_curve(y_test, dec_y_probas, ax=ax)
plt.show()

Roc curve python

Python

Lines of Code : 4

License : Strong Copyleft (CC BY-SA 4.0)

Copy

import scikitplot
scikitplot.metrics.plot_roc_curve(y_true, y_probas)
plt.show()

Community Discussions

Trending Discussions on scikit-plot

Google Cloud Function: FunctionsError: OperationError: code=13, message=Function deployment failed due to a health check failure

Rendering a confusion matrix

QUESTION

Google Cloud Function: FunctionsError: OperationError: code=13, message=Function deployment failed due to a health check failure

Asked 2020-Sep-29 at 12:08

when deploying with the following bash command:

...

ANSWER

Answered 2020-Sep-29 at 12:08

Even if currently the logs don't provide any additional information, when removing:

Source https://stackoverflow.com/questions/64077614

QUESTION

Rendering a confusion matrix

Asked 2019-Aug-06 at 03:13

I am working with jupyterlab, specifically rendering a confusion matrix. However, when rendering the matrix, it seems as if there is something wrong because the figure is not fully rendered.

I already had installed the sklearn packages, but still the same problem. I tried different alternatives, but still rendering a snipped confusion matrix.

Below an example of a code that I know would render a proper confusion matrix.

...

ANSWER

Answered 2019-Aug-02 at 20:14

Do not pass the confusion matrix as input argument to the plotting function. You need to pass the y_test, y_pred and the confusion matrix will be calculated internally.

To plot it use this:

Source https://stackoverflow.com/questions/57329189

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

Vulnerabilities

No vulnerabilities reported

Install scikit-plot

Installation is simple! First, make sure you have the dependencies Scikit-learn and Matplotlib installed. Or if you want the latest development version, clone this repo and run. at the root folder.