Clustering
Effective Data Analysis Strategies
Concepts
Data Mining Techniques for Anomaly Detection
Data Mining and Behavioral Analysis
Exploring Data Patterns
Models
Machine Learning Techniques for Data Analysis
Data Mining Applications in Smart Cities 
GPS Data Predictive Analytics Forecast traffic congestion Sensor Data
Clustering Optimize traffic light timings 2
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Effective Data Analysis Strategies Clustering: Grouping similar data points based on characteristics
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Concepts Clustering: Grouping a set of objects in such a way that objects in the same group are more similar than those in other groups
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Data Mining Techniques for Anomaly Detection Can handle large datasets, adaptable Requires labeled data, complex models
Clustering Techniques Groups data points into clusters and identifies points that do not belong to any cluster
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Data Mining and Behavioral Analysis Clustering: Grouping a set of objects in such a way that objects in the same group are more similar than those in other groups
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Exploring Data Patterns Clustering: Groups of data points that exhibit similar characteristics
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Models Stock market analysis, economic forecasting
Clustering A technique for grouping similar data points together
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Machine Learning Techniques for Data Analysis segmentation Anomaly detection Common Algorithms Algorithm Description K-Means
Clustering Partitions data into K distinct clusters based on feature similarity
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Data Mining for Analyzing Advertising Effectiveness Clustering: Grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups
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Data Mining Techniques: Common data mining techniques include
clustering, classification, regression, and association rule learning
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