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Linear Regression Models
Another widely used analysis method originating from statistics is linear regression. Since many application problems require the prediction of a...
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Valorization of waste pond ash in cement mortars and prediction of mechanical properties by simple linear regression
Pond ash disposal in open fields is a major environmental concern due to huge land requirements. One of the approaches to utilizing pond ash is by...
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Processing the Missing Value Based on the Linear Regression Approach
The problem of missing data is quite common, so solving the problem of missing values is necessary to greatly improve our data mining and analysis...
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Bayesian multiple linear regression model for GDP in India
Gross Domestic Product (GDP) known as the pulse of economy for any country depends on multiple factors like export–import, inflation rate and...
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Multi-time Step Deterioration Prediction of Freeways Using Linear Regression and Machine Learning Approaches: A Case Study
Multi-time step deterioration prediction of road pavements can provide more options for effective maintenance and rehabilitation decision under...
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Extended virtual reality based memory enhancement model for autistic children using linear regression
Extended Virtual Reality has expanded its wings to almost each and every sector enabling immersive experience in various fields and has found...
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Optimal Backfilling Materials with High Compressive Strength Based on Multiple Linear Regression
Backfilling material such as tailing (mine wastes) mixing with cement or gypsum has grown throughout the world’s underground mines. However, despite...
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Regression
Regression estimates the relationship between dependent variables and independent variables. This allows us to understand how changes in the...
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Development of Road Safety Models by Using Linear and Logistic Regression Modeling Techniques
Road accidents are caused by many factors like alcohol consumption, uncontrolled vehicle speed, poor road surface conditions, bad weather, inadequate...
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Efficient Correlation Method for Satellite Thermal Analysis Model Using Multiple Linear Regression and Optimization Algorithms
As the thermal analysis model of satellites is used as an important indicator for thermal design, it must accurately simulate the thermal behaviour...
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Model Predictive Control Strategy Based on Linear Regression for Wave Energy Converter
Implementing model predictive control (MPC) on the energy maximization control problem of wave energy converters (WECs) requires accurate prediction...
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Differentially Private Distributed Online Linear Regression over a Time-Varying Network
This paper investigates the problem of private distributed online linear regression over a time-varying network consisting of several connected...
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Linear and non-linear bayesian regression methods for software fault prediction
Faults are most likely to occur during the coding phase of software development. If, before the testing process, we can predict parts of code that...
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Improved Heteroscedasticity-Consistent Ridge Estimators for Linear Regression with Multicollinearity
This paper formalizes ridge estimators that specifically address the simultaneous presence of multicollinearity and heteroscedasticity in the data....
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Linear Methods
In this chapter, we will focus on the most simple methods in machine learning, viz., linear methods. Even if linear methods are relatively easy to...
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Detecting Outliers and Influential and Sensitive Observations in Linear Regression
This chapter reviews diagnostic and robust procedures for detecting outliers and other interesting observations in linear regression. First, we...
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Eliminating collinearity observed in chemical mass balance analysis using multi linear regression and synthetic receptor source profile dataset
Getting accurate source contribution results through Chemical Mass Balance (CMB) analysis requires unique and specific elemental species...
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Limited Memory Bundle Method for Clusterwise Linear Regression
A clusterwise linear regression problem consists of finding a number of linear functions each approximating a subset of the given data. In this...
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Dynamic Bandwidth Allocation Using Linear Regression Model in IOT with Machine Learning Techniques
An improved dynamic bandwidth allocation (IDBA) technique is presented for optimal bandwidth management provisioning in IoT devices. Although there...
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Intensive Review of Drones Detection and Tracking: Linear Kalman Filter Versus Nonlinear Regression, an Analysis Case
In this paper, an extensive review for objects and drones (AUVs) detection and tracking is presented. The article presents state of the art methods...
