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What is one of the educational tasks that can be performed using data mining EDM?
What is the purpose of creating a training model and testing model in data mining?
What is an example of classification of uncertain data in data mining?
How can data mining be used in the pharmaceutical sector?
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What is one of the ways data mining can be used in the insurance sector?
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What is one of the applications of data mining in the transportation sector?
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What is the purpose of data mining in the healthcare sector?
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What is one of the benefits of using data mining?
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What is the purpose of splitting the data set into two sets in data mining?
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What is one of the applications of data mining in a consumer merchandise organization?
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Study Notes
Data Mining: Introduction
- Data mining is the process of extracting knowledge or insights from large amounts of data using various statistical and computational techniques.
- Data can be structured, semi-structured, or unstructured, and can be stored in various forms such as databases, data warehouses, and data lakes.
Goals of Data Mining
- The primary goal of data mining is to discover hidden patterns and relationships in the data that can be used to make informed decisions or predictions.
Applications of Data Mining
- Data mining has a wide range of applications across various industries, including marketing, finance, healthcare, and telecommunications.
- Examples of data mining applications include:
- Identifying customer segments and target marketing campaigns in marketing
- Identifying risk factors for diseases and developing personalized treatment plans in healthcare
Data Mining Process
- The data mining process is broken into the following steps:
- Step 1: Understand the Business
- Step 2: Understand the Data
- Step 3: Prepare the Data
- Step 4: Build the Model
- Step 5: Evaluate the Results
- Step 1: Understand the Business
Data Mining Techniques
- Data mining techniques include:
- Clustering
- Classification
- Regression analysis
- Association rule mining
- Anomaly detection
Use Cases of Data Mining
- Market basket analysis: analyzing data on customer purchases to identify items that are frequently purchased together
- Predicting students' admission, profiling, and performance in higher education
- Research: predicting, classification, clustering, associations, and grouping of data
Industry Applications
- Healthcare and Insurance: examining new deals force activity, predicting customer behavior, identifying fraudulent behavior, and claims analysis
- Transportation: identifying best prospects for services, improving business cycle, and analyzing loading patterns
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Description
Learn about data mining, its process, and goals. Discover how to extract knowledge from large amounts of data using statistical and computational techniques.
