evaluation of prediction of binary, multiclass and regression
Project description
# DATS6450-final-project
---
This package is visualization for evaluation of prediction and performances of machine learning models based on the target variables and models' prediction.
There are three types of model prediction:
* Binary classification Evaluation
* Multiclass classification Evaluation
* Regression Evaluation
## Installation
You can install `prediction_evaluation` with `pip`:
`# pip install prediction_evaluation `
## The models:
---
### 1. Binary classification
* Confusion matrix plot
* ROC score and AUC plot
* Precision, recall and f1-score score table
### 2. Multi-class classification
* Confusion Matrix
* ROC score and AUC plot
* Precision, recall and f1-score score table
### 3. Regression
* Mean absolute error (MAE)
* Mean Squared error (MSE)
* R^2 score
* Residual plot
<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.
---
This package is visualization for evaluation of prediction and performances of machine learning models based on the target variables and models' prediction.
There are three types of model prediction:
* Binary classification Evaluation
* Multiclass classification Evaluation
* Regression Evaluation
## Installation
You can install `prediction_evaluation` with `pip`:
`# pip install prediction_evaluation `
## The models:
---
### 1. Binary classification
* Confusion matrix plot
* ROC score and AUC plot
* Precision, recall and f1-score score table
### 2. Multi-class classification
* Confusion Matrix
* ROC score and AUC plot
* Precision, recall and f1-score score table
### 3. Regression
* Mean absolute error (MAE)
* Mean Squared error (MSE)
* R^2 score
* Residual plot
<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Close
Hashes for prediction_evaluation-0.0.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | c2ae6541b52454cdcb26eb7d54d2849ec9a984bbda48fdd06ecab02443f2201f |
|
MD5 | 6470acf5356e93be514db0ce266f5e6a |
|
BLAKE2b-256 | d86705a01322c1370a1075919d57e52adc3da5bbc5d1dc29646c084a8216ce38 |