Evaluating the performance of the ML model is an very essential part of any project. There are many different evaluating metrics for regression and classification models. In this blog, we will learn about metrics for the regression model.
The regression model has many popular metrics to evaluate model performance. Performance metrics for any model should be chosen based on its objective, domain and goals. Below are some metrics for evaluating the performance of the regression model:
Linear Regression is a supervised machine learning algorithm where the predicted output is continuous and has a constant slope. The linear regression model has a linear relationship between the dependent and independent variable.
Let x be the independent variable and y be the dependent variable. We will define a linear relationship between these two variables as follows:
y = a_0 + a_1*x
where a_1 is the slope of the line and a_0 is the y-intercept. This equation will be used for predicting the value of Y. …
In the previous article, I have discussed some basic data structure of python. In the article, you will learn about python data structure like stack, queue and dequeue and their implementation.
1. Stack: A stack (sometimes called a “push-down stack”) is an ordered collection of items where the addition of new items and the removal of existing items always takes place at the same end. This end is commonly referred to as the “top.” The end opposite the top is known as the “base.” The ordering principle of stack is called LIFO, last-in-first-out.
Python is a modern, easy-to-learn, object-oriented programming language. It has a powerful set of built-in data types. If you are new to python language, then this blog is will help you learn. This blog contains basic linear data structure of python.
Operation performed on the list:
2. Tuple: They are very similar to…