Missing data analysis: where’s your missing piece?
Why missing data occurs can be attributed to various reasons, including human error, malfunctioning equipment, or even intentional omission. It…
Imputation using SoftImpute in python
SoftImpute is a matrix completion algorithm in Python that allows you to fill in missing data in your dataset. This…
Multiple Imputation with Chained Equations method & Python codes
MICE (Multiple Imputation by Chained Equations) is a statistical method used for handling missing data by creating multiple imputations or…
K-Nearest Neighbors (KNN) imputation in sklearn
K-Nearest Neighbors (KNN) imputation is another method to handle missing data. It uses the ‘k’ closest instances (rows) to each…
A comic guide to mean/median/mode imputation & Python codes
Handling missing data is a common preprocessing task in machine learning. In scikit-learn, you can handle missing data by using…
SVD for dimension reduction
Singular Value Decomposition (SVD) is a powerful matrix decomposition technique that generalizes the concept of eigenvalue decomposition to non-square matrices.…
test for outliers in multivariate data in Python
To test for outliers in multivariate data in Python, you can use several libraries like numpy, scipy, pandas, sklearn, etc. Here’s how you can…
Application of Bayesian theorem in spam detection & medical diagnosis
Example 1: Spam Detection Let’s say historically, 20% of emails are spam, so and the probability that the email is…