Citations issues
If you’ve added another author to your paper and posted it on arXiv, but Google Scholar doesn’t show the new author’s name in the citation, you can go to your paper listing in arxiv >>… Citations issues
A fun way to learn hypothesis testing: The spring roll issue
Hypothesis testing has diverse applications in medicine, economics, psychology, and sociology. It determines the effectiveness of new drugs in medicine, aids in data analysis for decision-making in economics, validates psychological theories, and analyzes societal trends in sociology. So, maybe this is a good time to wrap this topic up in your brain like a yummy spring roll!
Kernel tricks, SVM properties & kernel choice
Some popular types of kernels in SVM: 1. Linear Kernel 2. Polynomial Kernel 3. Radial Basis Function (RBF) Kernel (Gaussian Kernel) 4. Sigmoid Kernel Visualizing the decision boundaries To visualize the decision boundaries, we’ll use… Kernel tricks, SVM properties & kernel choice
Exponential distribution song
This song helps us better remember the properties of the exponential distribution. The exponential distribution models time between events in a Poisson process, where occurrences are independent at a constant rate. Key features include its probability density and cumulative distribution functions, mean, variance, and memoryless property. It has applications in queueing theory, reliability engineering, and survival analysis.
Phân ph?i m?
Phân ph?i m? (exponential distribution) là m?t phân ph?i xác su?t quan tr?ng trong lý thuy?t xác su?t và th?ng kê. Nó ???c s? d?ng ?? mô t? th?i gian gi?a các s? ki?n x?y… Phân ph?i m?
Recover lost content in Overleaf via history
In Overleaf, the history feature allows you to track and revert changes made to your document. This is particularly useful if you’ve inadvertently deleted something important. Here’s a step-by-step guide on how to use the… Recover lost content in Overleaf via history
Logistic Regression: method + Python & R codes
Logistic regression is a statistical method used for analyzing datasets in which there are one or more independent variables that determine an outcome. The outcome is typically a binary variable, meaning it has two possible… Logistic Regression: method + Python & R codes
AIC and BIC for Feature Selection
Akaike Information Criterion (AIC) Bayesian Information Criterion (BIC) Comparison and Use in Feature Selection By applying AIC and BIC in feature selection, we can make informed decisions about which features to include in their models,… AIC and BIC for Feature Selection
KNN classification: practical notices & implementation using Python & R
We should normalize or standardize data before applying KNN because the algorithm is distance-based, and unscaled features can distort distance calculations, leading to biased results. In this example, we’ll use the Iris dataset, which is… KNN classification: practical notices & implementation using Python & R
K-Nearest Neighbors (KNN): an introduction
K-Nearest Neighbors (KNN) is a popular algorithm used for both classification and regression tasks. In KNN, the output is a class membership, which is assigned based on the majority of the k nearest data points.… K-Nearest Neighbors (KNN): an introduction