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Multicollinearity occurs when two or more independent variables in a linear regression model are highly correlated. To address multicollinearity, here are a few simple str...
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How to know if "best fit line" really represents known set of data?
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To determine if a best-fit line accurately represents a dataset, we can the line and compare it through:Visual Inspection: Look at how the line fits the data. It should pa...
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Is least squares regression the same as linear regression
Last Updated: 12 November 2024
Yes, Least squares regression and linear regression are closely related in machine learning, but they’re not quite the same. Linear regression is a type of predictive mode...
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Can Linear Regression be used with Binary Independent Variables?
Last Updated: 25 November 2024
Yes, linear regression can work with binary independent variables, where the variable only takes two values, such as 0 and 1. These binary predictors are used to distingui...
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When to normalize data in regression?
Last Updated: 12 November 2024
Normalization, or scaling, is the process of adjusting the values of features to a common scale without distorting differences in the data. When working with regression mo...
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Does Linear Regression Require Feature Scaling?
Last Updated: 19 November 2024
Linear regression does not always require feature scaling, but scaling can improve its performance and help in specific cases. The main reason is that linear regression mo...
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How to Handle Categorical Variables in Regression
Last Updated: 09 December 2024
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What is Gradient descent?
Last Updated: 30 May 2025
Gradient Descent is a fundamental algorithm in machine learning and optimization. It is used for tasks like training neural networks, fitting regression lines, and minimiz...
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Poisson Regression
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Poisson regression is a statistical technique used to model and analyze count data, where the outcome variable represents the number of times an event occurs in a fixed in...
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