This post provides an in-depth understanding of False Discovery Rate (FDR) and the Benjamini-Hochberg Method, crucial in statistical analysis with large datasets like genomics. It explains FDR's role in identifying false positives in multiple hypothesis testing and the Benjamini-Hochberg Method's effectiveness in controlling FDR. The post compares various p-value adjustment methods, discussing their advantages, limitations, and suitability for different data types. It emphasizes the BH method's balance in statistical power and error control, and its integration in software like R, highlighting its applicability across scientific fields.

Evaluating the quality of classification

Navigating the world of sparse datasets is a fundamental skill in machine learning. This blog post delves into the challenges posed by sparse datasets, such as high dimensionality, overfitting, and computational inefficiency, offering insightful strategies to overcome them. With hands-on Python code snippets for visualization and implementation of solutions like dimensionality reduction, imputation, and regularization, this post is a comprehensive guide for anyone looking to harness the potential of sparse data in building robust machine learning models. Explore the intricacies of dealing with sparse datasets and equip yourself with the knowledge to turn challenges into opportunities!

The Fruchterman-Reingold layout is a force-directed layout algorithm, which treats edges like springs that move vertices closer or further from each other in an attempt to find an equilibrium that minimizes the 'energy' of the system. © Bernie Hogan

NMF: Non-negtive matrix factorization

t-sne

Unsupervised Machine Learning in Python (DBSCAN; UMAP, t-SNE, etc)

Fourier Transforms

Statistic note for data scientists

What is Negative binomial and binomial distribution. $b(x; r, P) = C_{x-1}^{r-1} imes P^r imes (1 - P)^{x - r}$

What is binomial and binomial distribution. $b(x; n, P) = C_{n}^{x} * P^ x (1 - P)^{(n - x)}$

Odds of an event happening is defined as the likelihood that an event will occur, expressed as a proportion of the like...