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Showing posts from April, 2019

Business Value from Machine Learning Methods

Linear Regression - To make predictions for sales forecast, price optimization, marketing optimization, financial risk assessment. 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. Naive Bayes - Build spam detector, analyze customer sentiments, or automatically categorize products, customers or competitors. K-means clustering - Useful for cost modeling and customer segmentation Hierarchical clustering - Model business processes, or to segment customers based on survey responses, hierarchical clustering will probably come in handy. K-nearest neighbor classification - Type of instance based learning. use it for text document classification, financial distress prediction modeling, and competitor analysis and classification. Principal component analysis - Dimensionality reduction method that you can use for detecting fraud, for s...

Types of Data Analytics

In the order of their complexity, they can be classified in 4 types - Descriptive Analytics - Based on Historical & Current data answer question like - "What happened?" Diagnostic Analytics - For deducing & inferring success or failure, like - "Why that happened?" or "Why it went wrong?" or "Why did we receive this growth or success?" Predictive Analytics - Based on what happened or what is happening deriving the answer to question like "What will happen?". This involves complex model-building and analysis in order to predict a future event or trend. Prescriptive Analytics - Optimize processes, structures, and systems through informed action that's based on predictive analytics - what you should do based on what will happen.