In data analysis and machine learning practice, "dimensionality reduction" is an essential technique for visualizing high-dimensional data and as a preprocessing step for clustering. Representative ...

Bollinger Bands Trading Strategies: How to Read Volatility, Identify Market Regimes, and Trade with a Statistical Edge Commodity correlation isn’t static—and ignoring that can blow up your portfolio.

PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most ...

The ECO-SAM utilizes a pre-trained BERT encoder to obtain semantic embedding of input texts and then leverages a self-attention mechanism to model the semantic correlation between emotions.

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional ...

Principal Axis Factoring (PAF) is a statistical method used in factor analysis. It is a technique aiming to identify the underlying factors that explain the variance in data. Factor analysis is often ...

Correlation matrix is a table that shows the pairwise correlations between several variables. Each row and column in the table represents a variable, and the table itself shows the correlation between ...

清华大学出版社近期拟引进 Taylor & Francis Group今年出版的一本 利用Python实现统计和数据可视化类英文著作，该著作旨在为有兴趣在数据科学与分析以及一般统计分析领域的学生和从业人员提供统计学方面的桥梁。 我社计划翻译成中文出版，以应广大读者的需求 ...

Advanced measurement and data storage technologies have enabled high-dimensional profiling of complex biological systems. For this, modern multiomics studies regularly produce datasets with hundreds ...

I thought it was strange that I couldn't easily find a way to get both these weighted correlations with a single class/function in Python. So I made it myself. This class can be used in a few ...