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250 articles for “Regression”
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The Fundamental Premises of Efficient Linear Regression and Applying Regression
Abstract: Linear regression is a statistical technique for estimating the value of a dependent variable from an independent variable. Linear regression is a way to assess how two variables are related. A dependent variable is predicted using this modelling technique based on one or more independent factors. Many analyses are based on linear regression. Sometimes the data must be changed to satisfy the needs of the analysis, or extra room must …
Published in Trends in Machine design Read article
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Modeling Dispersed Count Data: Evaluating the Conway–Maxwell–Poisson Regression with COVID-19 Mortality Data
Abstract: Count data are prevalent in diverse fields such as biology, healthcare, psychology, and marketing, characterized by non-negativity and inherent heteroskedasticity, often exhibiting overdispersion or underdispersion. Traditional Poisson regression, which assumes equal mean and variance, is inadequate for such dispersed data. To address this, various generalized linear models (GLMs) and their extensions, including negative binomial (NB) and Conway–Maxwell–Poisson (CMP) regressions, are utilized. This study evaluates the performance of CMP regression compared …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 18–26 Read article
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Performance of Some Modified Ordinary Ridge Regression Estimators
Abstract: In multiple linear regressions, if the data suffer from severe multicollinearity, then the ordinary least squares (OLS) method become more sensitive to it, and in such a case OLS could yield wrong sign for some of the regression coefficients. Therefore, when such a situation arises, we could use one of the biased regression methods viz., ridge regression, principal component regression, and so on, as an alternative method to OLS. This …
Published in Research & Reviews : Journal of Statistics Read article
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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Climate Change Including Forest Fire Prediction using Machine Learning and Deep Learning
Abstract: Climate change alludes to long haul shifts in temperatures and atmospheric conditions. These movements might be regular, for example, through varieties in the sun-oriented cycle. In any case, since the 1800s, human exercises have been the fundamental driver of climate change, basically because of consuming fossil fuels like coal, oil and gas. Many individuals think climate change mostly implies hotter temperatures. Be that as it may, the temperature climb is …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Regression Analysis of Topological Indices and Physicochemical Properties of Polymer-Based Anticancer Drugs
Abstract: The research analyzed the quantitative correlation between topological indices and the physicochemical properties of selected anticancer compounds using regression analysis. Various topological descriptors—such as the First Zagreb Index, Second Zagreb Index, and Forgotten Index were calculated and regressed against key molecular features, including polar surface area, melting point, and molar refractivity. The regression analysis revealed linear correlations between these topological indices and the properties of anticancer drugs, with particularly strong …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 255–267 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Past Life Regression and Psychiatry: A Critical Analysis
Abstract: Past Life Regression (PLR) is a controversial therapeutic approach. It is done through hypnosis, which recovers memories of previous lives. Although PLR has gained some popularity in alternative medicine, it is heavily criticized in mainstream psychiatry. As the effects have not been empirically validated. This study provides a comprehensive exploration of Past Life Regression (PLR), offering insights into how it can be understood within the realm of psychiatry. It delves …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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An Empirical Analysis of Cost, Time, and Quality Relationships Using Correlation and Regression Techniques
Abstract: Cost, time, and quality have been recognized as the three key dimensions that determine construction project performance and are commonly represented through the "Project Management Triangle." However, despite their theoretical linkage, there is limited empirical evidence to quantify the nature of their relationships, particularly within developing construction markets. This paper seeks to contribute to addressing this shortfall by investigating the specific influence of cost and schedule variations upon quality outcomes …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 52–60 Read article
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Experimental and Polynomial Regression Modelling of Tensile Characteristics of Hybrid Jute/Hemp Fiber Composites
Abstract: The present study aims to develop hybrid jute-hemp fiber/epoxy composites by the hand lay-up process with 60% of fiber reinforcement and 40 % of matrix ratio. To measure the change of tensile properties, prepared hybrid composites were tested for normal tensile strength and edge notch tensile (ENT) test as per the ASTM standards. Findings show that, developed composites with reported tensile strength followed by comparing it with fracture toughness. Experimentally, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 47–58 Read article
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User App Segmentation for Better Understanding of Reviews and Password Resets Using Regression
Abstract: In today’s digital landscape, understanding users’ needs and behaviors is key to improving app experiences. This paper focuses on how we can better understand user reviews and password resets in mobile apps through a method called user segmentation. By dividing users into groups based on their feedback and password reset patterns, we aim to uncover insights that can enhance app design and security. Using a mix of user reviews and …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 1–9 Read article
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Comparative Analysis of Polyethylene Terephthalate Based Blended Lean Mortar Mixes by Applying Mathematical Simulations and Regression Approach
Abstract: Currently, construction manufacturing units need an abundant number of non-renewable resources rising in the quarrying of natural strata, producing a disparity in our precious environment. Besides this, a plentiful amount of waste material like plastic waste in several forms such as solid, filler, etc., is generated gradually. Therefore, efficient sustainable disposal seemed like a threatening mission across the world. To mitigate the issue, in the present investigation, fine aggregate (sand) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 60–70 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Parametric Study of Laser Drilling Process Using Multi Variable Regression Analysis
Abstract: The laser drilling process is an advanced manufacturing technique extensively employed for intricate and high-value components in aerospace, automotive, and electronics industries. Laser drilling technology offers opportunities to meet the contemporary demands of industries using a broad spectrum of engineering materials. However, this process encounters several engineering challenges such as thermal damage, dimensional inaccuracies, and the formation of a recast layer in the drilled components. This study focuses on examining …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1000–1015 Read article