> For the complete documentation index, see [llms.txt](https://mugdha-thanawala.gitbook.io/tkmt_package/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://mugdha-thanawala.gitbook.io/tkmt_package/guides/performance-evaluation/regression.md).

# Regression

Performance Evaluation

Shows the performance of the model in terms of accuracy, MAE, MSE,MAPE and RMSE.

{% hint style="info" %}
`Evaluation.performance_evaluation(true, pred)`
{% endhint %}

```python
   Parameters 
      ---------- 
      true: actual test output. 
      pred: predicted test output.
      Attributes
      ----------
      y_test: actual test output. 
      y_test_pred: predicted test output

      Example
      -------
      >>> from tkmt_package.evaluation import Evaluation
      >>> eva = Evaluation()
      >>> eva.performance_evaluation(y_test, y_test_pred)
```

Graphical Representation

{% hint style="info" %}
`Evaluation.get_plot_regression(true, pred, ascending, label)`
{% endhint %}

Plots the actual vs predicted output graph.

```python
Parameters
-----------
true: actual output
pred: predicted output
ascending:            
label: true value and predicted value label

Attributes
----------
y_test: actual test output. 
y_test_pred: predicted test output.

Example
-------
>>> from tkmt_package.evaluation import Evaluation
>>> eva = Evaluation()
>>> true, pred = eva.get_plot_regression(true= y_test, pred=y_test_pred, 
                 ascending= False, label= "Discharge_Capacity")
```