In this article we are going to develop pseudocode for Linear Regression Method so that it will be easy while implementing this method using high level programming languages.

Apr 5, 2025 · Linear regression is also a type of supervised machine-learning algorithm that learns from the labelled datasets and maps the data points with most optimized linear functions which can be used for prediction on new datasets.

Oct 1, 2020 · Linear Regression is a supervised learning algorithm which is both a statistical and a machine learning algorithm. It is used to predict the real-valued output y based on the given input value x. It depicts the relationship between the dependent variable y and the independent variables x i ( or features ).

Sep 4, 2022 · Here we’ll be exploring the simple linear regression and its key ideas intuitively along with the pseudo-code and python implementation. Before getting to Linear Regression or any kind of regression per se, it’s crucial to understand the concept of Regression Modeling.

Linear Regression is a supervised machine learning algorithm that learns a linear relationship between one or more input features (X) and the single output variable (Y). As a standard paradigm of Machine Learning, the output variable is dependent on the input features.

Mar 2, 2021 · Linear regression is one of the easiest and most popular Machine Learning algorithms. It is a statistical method that is used for predictive analysis. Linear regression makes predictions for...

Jan 6, 2023 · Linear regression works by creating a linear line (in the form y=mx+b) to most accurately predict the value of dependent variables by solving for values m (slope) and b (y-intercept). To do this, models use a method known as least squares in order to most accurately find the line of best fit.

Jan 13, 2025 · Linear regression is one of the simplest and most widely used statistical models. This assumes that there is a linear relationship between the independent and dependent variables. This means that the change in the dependent variable is proportional to the change in the independent variables.

Supervised Learning: Regression Problem: Predict real-valued output. Remember that classification (not regression) refers to predicting discrete-valued output .

In this article, we will dive into linear regression and provide engaging, real-world examples from domains like finance, banking, and retail—all complemented by Python code to help you get started. What is the Linear Regression Algorithm?