Part II: Unsupervised machine learning in R to cluster and identify candidate countries for international expansion, using PCA, K-Means, and DBSCAN.

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Unlike PCA (maximum variance) or ICA (maximum independence), ForeCA finds components that are maximally forecastable. This makes it ideal for time series analysis where prediction is often the primary ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

The authors present a critique of current usage of principal component analysis in geometric morphometrics, making a compelling case with benchmark data that standard techniques perform poorly. The ...

Sentiment analysis, i.e., determining the emotional tone of a text, has become a crucial tool for researchers, developers, and businesses to comprehend social media trends, consumer feedback, and ...

The Basics of Returns-Based Style Analysis Fetching Data for Style Analysis Case Study: Looking for Investment Style Drift Unlock More Code Snippets for Rigorous Fund Evaluation Investors choose funds ...