Predictive Analytics I: Data Mining Process, Methods, and Algorithms - Data Mining Concepts and Applications
3 important questions on Predictive Analytics I: Data Mining Process, Methods, and Algorithms - Data Mining Concepts and Applications
Define Data Mining. Why are there many different names and definitions for data mining?
Is the process through which previously unknown patterns in data were discovered.
Software vendors wanted to include in the definition most forms of data analysis in order to increase sales with the popularity of the data mining label.
Software vendors wanted to include in the definition most forms of data analysis in order to increase sales with the popularity of the data mining label.
What are some major data mining methods and algorithms?
The major data mining methods:
- Prediction
- Association
- Segmentation
- Decision trees
- Neural Networks
- Logistic regression
- discriminant analysis
- Support Vector Machines
- Genetic algorithms
What are the key differences between the major data mining tasks?
Classification: objective is to analyze the historical data stored in a database and automatically generate a model that can predict the future behaviour
Clustering: partitions a collection of things. the class labels are unknown (unlike in classification)
Associations: objective is discover interesting relationshilps among variables in large databases.
Clustering: partitions a collection of things. the class labels are unknown (unlike in classification)
Associations: objective is discover interesting relationshilps among variables in large databases.
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