Classify
Data Mining Techniques for Product Recommendations
Data Mining for Measuring Campaign Success
Semantic Analysis
Predictive Models in Data Mining
Cost Analysis
Predictive Modeling
Detection
Understanding the Data Mining Process 
Modeling Applying various algorithms and techniques to build models that can predict or
classify data
...
Data Mining Techniques for Product Recommendations Algorithms like decision trees, support vector machines, and random forests can be applied to
classify user preferences based on historical data
...
Data Mining for Measuring Campaign Success For example, businesses can
classify customers as 'responders' or 'non-responders' based on their interaction with a campaign
...
Semantic Analysis Entity Recognition: Identifying and
classifying key entities (such as people, organizations, and locations) within the text
...
Predictive Models in Data Mining Linear Regression, Logistic Regression Classification Models Used to
classify data into discrete categories
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Cost Analysis Classify Costs: Categorize costs into fixed, variable, direct, and indirect costs
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Predictive Modeling Linear Regression, Logistic Regression Classification Models Used to
classify data into categories based on predictor variables
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Detection Named Entity Recognition (NER): Identifying and
classifying key entities in text
...
Definition Named Entity Recognition (NER): A technique used to identify and
classify key entities in text, such as names of people, organizations, and locations
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Understanding Brand Perception through Text Data Sentiment Classification: Using algorithms to
classify the sentiment of each text entry
...
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