Abstract: This paper focuses on a multidimensional indicator prediction assessment method based on time series and multiple linear regression modelling. Through in-depth analysis of relevant data, ...

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The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, years of experience, and so on ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, high school grade point ...

Amid the wave of the digital age, advanced technologies such as big data, artificial intelligence, and cloud computing are driving precise analysis and forecasting across various fields. This paper ...

This project implements Multiple Linear Regression using Gradient Descent in pure Python (without external libraries like NumPy or Scikit-learn). The goal is to train a model that predicts an output ...

Background: The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP). Conclusion: This ...

Linear regression may be the most basic and accessible machine learning (ML) algorithm, but it’s also one of the fastest and most powerful. As a result, professionals in business, science, and ...

Abstract: This paper presents a comprehensive exploration of earthquake magnitude and depth prediction using an advanced machine learning model and multiple linear regression model. The study ...