# A Guide to Evaluate ML Model’s Performance in Python?

## A Practical Approach to Compute the Model’s Performance and Implementation in Python covering all Mathematical Reasonings. Explained!

Welcome! Are you ready with your cool machine learning model trained on millions of data points and now you want to test its performance but you don’t know where to start with or what could be a better way to do so?

In this article, we would be discussing everything you need to know to test your model’s performance whether it be a **Classification **model or a **Regression **model, in this article we will dive deep into the understanding of the machine learning model evaluation process which is indeed a very crucial step for a Machine Learning Engineer or a Data Scientist.

So let’s get started!

## Classification Algorithms Evaluation

Let’s start with the understanding of how we can evaluate a classification algorithm. A classification model predicts the output as a class label. Let us assume there is a random variable ‘**xᵢ**’, so the predicted value of **xᵢ **is ‘**yᵢ**’ labeled as:

yᵢ ∈ {class1, class2, class3, …}