Multivariate Analysis - Tag - Zhiverse

Multi-dimensional Scaling

Author — Thu, 15 May 2025 15:58:34 +0800

Multi-dimensional Scaling (MDS) is a dimensionality reduction technique that calculates pairwise distances between objects in a dataset and represents them in a lower-dimensional space while preserving the original relative distance structure. MDS can be seen as a method for visualizing data to intuitively observe the relative relationships between data points.

Dataset Exploration and Analysis #2

Author — Mon, 28 Apr 2025 19:51:50 +0800

Principal Component Analysis (PCA)

Author — Tue, 25 Mar 2025 15:09:49 +0800

Principal Component Analysis (PCA) is a commonly used dimension reduction method. It transforms an originally linearly dependent dataset into a set of linearly independent new variables through an orthogonal transformation. This process minimizes the loss of information when projecting the dataset onto these new variables. These new variables are ranked based on their variance, with the one having the highest variance called the first principal component, the second highest called the second principal component, and so on. PCA is widely used to map high-dimensional data into lower-dimensional space while preserving as much of the original data’s key features and information as possible.

Dataset Exploration and Analysis

Author — Tue, 18 Mar 2025 12:58:27 +0800

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.