R - Tag - Zhiversehttps://yao-chih.netlify.app/en/tags/r/R - Tag - ZhiverseHugo -- gohugo.ioenyaochihh@gmail.com (Josh)yaochihh@gmail.com (Josh)ZhiverseSun, 08 Mar 2026 14:32:23 +0800The Analysis of Characters in Dream of the Red Chamberhttps://yao-chih.netlify.app/en/the-analysis-of-characters-in-dream-of-the-red-chamber/Tue, 23 Dec 2025 10:28:34 +0800Authorhttps://yao-chih.netlify.app/en/the-analysis-of-characters-in-dream-of-the-red-chamber/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/The%20Analysis%20of%20Characters%20in%20Dream%20of%20the%20Red%20Chamber/cover%20image.webp" referrerpolicy="no-referrer"> </div>Classical Chinese novels are an indispensable and important part of Chinese literature, with many masterpieces throughout history worthy of in-depth exploration. Among them, Dream of the Red Chamber is regarded as one of the representative works of classical Chinese fiction and possesses a high degree of scholarly interest. The fates of the characters and the numerous events in the novel are intricately and closely interconnected, requiring thorough study to fully understand their true significance.Global Spatiotemporal Data: Exploring and Downloading Resources from NASA GES DISChttps://yao-chih.netlify.app/en/global-spatiotemporal-data-exploring-and-downloading-resources-from-nasa-ges-disc/Sat, 29 Nov 2025 21:53:36 +0800Authorhttps://yao-chih.netlify.app/en/global-spatiotemporal-data-exploring-and-downloading-resources-from-nasa-ges-disc/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Global%20Spatiotemporal%20Data%20Exploring%20and%20Downloading%20Resources%20from%20NASA%20GES%20DISC/cover%20image.png" referrerpolicy="no-referrer"> </div>GES DISC is a scientific data center under NASA that preserves Earth science–related data and provides free access to all users, making it an excellent source for obtaining spatiotemporal data.Notes on Creating Python Moduleshttps://yao-chih.netlify.app/en/notes-on-creating-python-modules/Mon, 13 Oct 2025 19:40:04 +0800Authorhttps://yao-chih.netlify.app/en/notes-on-creating-python-modules/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Notes%20on%20Creating%20Python%20Modules/cover%20image.webp" referrerpolicy="no-referrer"> </div>Recently, I've been learning how to package Python code for quick sharing and easy installation. After exploring various distribution methods, I realized that creating a Python module is probably one of the most convenient options, mainly because it saves me from having to reinstall everything repeatedly.Understanding the Confusion Matrixhttps://yao-chih.netlify.app/en/understanding-the-confusion-matrix/Fri, 21 Mar 2025 18:04:29 +0800Authorhttps://yao-chih.netlify.app/en/understanding-the-confusion-matrix/<div class="featured-image"> <img src="https://raw.githubusercontent.com/Josh-test-lab/website-assets-repository/refs/heads/main/posts/Understanding%20the%20Confusion%20Matrix/cover%20image.png" referrerpolicy="no-referrer"> </div>In machine learning, we can build various models, ranging from simple linear regression to complex neural network models. These models can be applied to different fields, such as image recognition, language generation, and financial forecasting. Each model has its advantages and applicable scenarios. For example, linear regression is suitable for fitting and analyzing datasets with target variables, while deep learning can handle complex nonlinear datasets. However, how do we assess the quality of a model? Simply relying on accuracy may not be sufficient to evaluate model performance, especially in cases with imbalanced class distributions. Therefore, we use **Confusion Matrix** to analyze the performance of classification models.Dataset Exploration and Analysishttps://yao-chih.netlify.app/en/dataset-exploration-and-analysis/Tue, 18 Mar 2025 12:58:27 +0800Authorhttps://yao-chih.netlify.app/en/dataset-exploration-and-analysis/

The cover image is generated by ChatGPT, depicting data analysis. The prompt used is “A modern data analysis concept illustration featuring a futuristic workspace. The image includes multiple data charts, graphs, and dashboards displayed on transparent holographic screens. A diverse team of analysts and data scientists collaborate, analyzing trends and insights on large monitors. The scene has a sleek, high-tech atmosphere with glowing blue and purple hues, reflecting a professional and cutting-edge environment.” 。

Introduction

The dataset used in this analysis is the Swiss bank notes dataset, which is utilized by banks to distinguish between genuine and counterfeit old Swiss Francs. This study downloads the bank2.dat dataset from https://github.com/QuantLet/MVA/tree/master/QID-1530-MVAscabank56 and conducts the analysis using the R programming language.

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