Principles of Data Mining (Undergraduate Topics in Computer Science)

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ASIN ‏ : ‎ B0891SJWV1
Publisher ‏ : ‎ Springer; 4th edition (May 20, 2020)
Publication date ‏ : ‎ May 20, 2020
Language ‏ : ‎ English
File size ‏ : ‎ 59315 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 842 pages

Principles of Data Mining (Undergraduate Topics in Computer Science)

Data mining is a crucial skill in today’s technology-driven world, allowing us to extract valuable insights and patterns from large datasets. In this post, we will explore the fundamental principles of data mining that are essential for undergraduate students in computer science.

1. Data Preprocessing: Before we can start mining valuable information from data, we must first preprocess and clean the data. This includes handling missing values, removing outliers, and normalizing the data to ensure accurate and reliable results.

2. Data Exploration: Once the data is preprocessed, we can start exploring it to identify patterns and trends. This involves using statistical techniques, visualization tools, and machine learning algorithms to gain a deeper understanding of the data.

3. Data Mining Techniques: There are various data mining techniques that can be used to extract valuable information from data, such as classification, clustering, association rule mining, and anomaly detection. Each technique has its own strengths and weaknesses, and it is important to choose the right technique for the specific problem at hand.

4. Evaluation and Validation: It is crucial to evaluate the performance of our data mining models to ensure their accuracy and reliability. This involves using metrics such as accuracy, precision, recall, and F1-score to assess the performance of our models and validate their results.

5. Ethical Considerations: In the age of big data, it is important to consider the ethical implications of data mining. This includes ensuring data privacy, maintaining data security, and being transparent about how data is being used and shared.

By understanding these fundamental principles of data mining, undergraduate students in computer science can develop the skills and knowledge needed to extract valuable insights from data and make informed decisions in a data-driven world.
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