Beginner’s Guide to Regression Decision Trees
Regression trees offer a manageable entry point for beginners in data science and machine learning due to their simplicity and interpretability.
Martin Solomon
Beginner’s Guide to Classification Decision Trees
classification decision trees offer a robust and intuitive method for data categorization in machine learning.
The Basic Foundations of Decision Trees
Whether it’s assessing credit risk, diagnosing medical conditions, segmenting customers for targeted marketing, or predicting real estate prices, decision trees offer a reliable and accessible approach for data-driven decision-making across various domains.
Beginner’s Guide to Logistic Regression
Logistic regression stands out as an essential tool in the statistical modeling and machine learning landscapes, offering a robust and interpretable framework for tackling binary and multinomial classification problems.
Beginner’s Guide to Elastic Net Regression
Elastic Net Regression is a regularization technique used in linear regression models. It combines two popular methods: Lasso (Least Absolute Shrinkage and Selection Operator) and Ridge Regression. The primary goal of Elastic Net, like Lasso and Ridge, is to prevent overfitting, which often occurs in models with many predictors. In this section, I’ll share the … Read more
Beginner’s Guide to LASSO Regression
LASSO Regression, short for Least Absolute Shrinkage and Selection Operator, is a method of linear regression that incorporates a regularization term. This technique is highly regarded in the data science community, especially in areas like machine learning, for its dual capacity to carry out variable selection and regularization. These features significantly improve the prediction accuracy … Read more
Beginner’s Guide to Ridge Regression
Ridge regression is a technique used to enhance the estimation of coefficients in linear regression models, especially when the predictor variables are multicollinear—meaning they are highly correlated with one another. This multicollinearity can cause problems in ordinary least squares (OLS) regression, such as inflated variances and unreliable parameter estimates. In this section, we’ll understand what … Read more
Beginner’s Guide to Polynomial Regression
Polynomial regression is a form of regression analysis in which the relationship between the independent variable \(x\) and the dependent variable \(y\) is modeled as an \(n\)th degree polynomial. Polynomial regression fits a nonlinear relationship between the value of \(x\) and the corresponding conditional mean of \(y\), denoted \(E(y|x)\). This regression algorithm has been used … Read more
Beginner’s Guide to Multiple Linear Regression
Multiple Linear Regression models the relationship between one dependent variable and two or more independent variables.
Beginner’s Guide to Simple Linear Regression
Welcome to the Beginner’s Guide to Simple Linear Regression—a key starting point in the world of Machine Learning. If you’re new to this field, don’t worry. We’re here to make things easy and fun. So, what’s linear regression? It’s basically a tool we use to understand relationships between different things. Think of it as the … Read more