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Business Value from Machine Learning Methods


  1. Linear Regression - To make predictions for sales forecast, price optimization, marketing optimization, financial risk assessment.
  2. Logistic Regression - To predict customer churn, to predict response versus advertisement spending, predict lifetime value of customer, and to monitor how business decisions affect predicted churn rates.
  3. Naive Bayes - Build spam detector, analyze customer sentiments, or automatically categorize products, customers or competitors.
  4. K-means clustering - Useful for cost modeling and customer segmentation
  5. Hierarchical clustering - Model business processes, or to segment customers based on survey responses, hierarchical clustering will probably come in handy.
  6. K-nearest neighbor classification - Type of instance based learning. use it for text document classification, financial distress prediction modeling, and competitor analysis and classification.
  7. Principal component analysis - Dimensionality reduction method that you can use for detecting fraud, for speech recognition, and for spam detection.  

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