Unsupervised Learning: Transformations and Clustering Methods

Posted by on Feb 9, 2026 in Dance Sciences | 0 comments

Unsupervised Learning Transformations and Clustering

1. Purpose of Unsupervised Transformations

Unsupervised transformations create a new representation of the data that is easier to interpret or use than the original raw data.

2. Application of Dimensionality Reduction

Dimensionality reduction simplifies high-dimensional data while preserving the most important information.

3. Role of Clustering Algorithms

Clustering algorithms group data into clusters based on similarity, revealing hidden structure

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Data Mining Fundamentals and KDD Process

Posted by on Dec 28, 2025 in Dance Sciences | 0 comments

1. Data Mining Definition and Applications

Data Mining is the process of automatically discovering meaningful patterns, trends, and relationships from large datasets using statistical, machine learning, and database techniques.

Applications:

  • Market Basket Analysis
  • Fraud Detection

(Other examples: customer segmentation, medical diagnosis, recommendation systems)

2. Knowledge Discovery in Databases (KDD)

KDD is the overall process of extracting useful knowledge from data. It involves several steps such as

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