Classification Metrics
Key Considerations for Predictive Analytics Implementation
Data Mining for Effective Collaboration
Data Governance for Compliance and Security
Plans
Data Visualization Fundamentals
Data Mining in Human Resources
Predictive Models
Methodology 
Internal Data: Data generated within the organization, such as sales records, customer interactions, and operational
metrics ...Decision Trees A graphical representation of decisions and their possible consequences, used for
classification and regression
...
Key Considerations for Predictive Analytics Implementation include: What specific problems do we want to solve? What decisions will be informed by predictive analytics? What
metrics will be used to evaluate success? 2
...classification, regression) The complexity of the model vs
...
Data Mining for Effective Collaboration similar data points together Identifying team members with complementary skills
Classification Assigning items to predefined categories Segmenting teams based on performance
metrics Association
...
Data Governance for Compliance and Security It encompasses the processes, roles, policies, standards, and
metrics that ensure effective and efficient use of information in enabling an organization to achieve its goals
...Implement Data
Classification: Categorize data based on sensitivity and regulatory requirements
...
Plans classification, regression)
...These plans define
metrics and methods for evaluating model performance, including: Metric Description Accuracy Measuring the proportion of correct predictions made by the model
...
Data Visualization Fundamentals Model Evaluation: Visualizing performance
metrics to assess model effectiveness
...techniques for visualizing machine learning data include: Confusion Matrix: A table used to describe the performance of a
classification model
...
Data Mining in Human Resources Performance Management Data mining can enhance performance management through: Tracking employee performance
metrics over time
...human resources, including: Technique Description Application in HR
Classification Assigns items in a dataset to target categories or classes
...
Predictive Models include: Regression Models Linear Regression Logistic Regression
Classification Models Decision Trees Support Vector Machines (SVM) Random Forests Time Series Models
...Model Evaluation: Assessing the model's performance using
metrics such as accuracy, precision, recall, and F1 score
...
Developing Predictive Models with Accuracy Logistic Regression: Useful for binary
classification problems
...Evaluating Model Accuracy To ensure that predictive models are effective, various
metrics can be employed to evaluate their accuracy: Metric Description Accuracy The ratio of correctly predicted instances to the total instances
...
Key Considerations for Machine Learning Deployment Defining success
metrics to evaluate the model's performance
...classification, regression)
...
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