KNN classification: practical notices & implementation using Python & R
Kurious Fox We should normalize or standardize data before applying KNN because the algorithm is distance-based, and unscaled features can…
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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…
Linear Discriminant Analysis Implementation in Python & R
Linear Discriminant Analysis (LDA) is a classifier that creates a linear decision boundary by fitting class-conditional densities to…
Stepwise Feature Selection +example
Stepwise feature selection is a systematic approach to identifying the most relevant features for a predictive model by…
Backward feature selection + example
Backward feature selection involves iteratively removing the least significant feature from a model based on adjusted R-squared. In…
Forward feature selection: a step by step example
Forward feature selection starts with an empty model and adds features one by one. At each step, the…
ElasticNet Regression: Method & Codes
ElasticNet regression is a regularized regression method that linearly combines both L1 and L2 penalties of the Lasso…
Ridge regression: method & R codes
Motivation Now, recall that for LASSO Ridge Regression: Ridge regression: Ridge adds the penalty, which is the sum…
Lasso Regression and LassoCV: methods & Python codes
The Lasso (Least Absolute Shrinkage and Selection Operator) is a regression technique that enhances prediction accuracy and interpretability…
How to Write a Proof in a paper
Reviewers are not required to read supplementary materials, but many do. Therefore, making your proof easy to read…