Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A multi-class classification problem is one where the goal is to predict the ...

What is a ‘random forest’?

Discover how random forests, a machine-learning technique, enhance prediction accuracy by combining insights from multiple ...
Forbes

What Are The Advantages Of Logistic Regression Over Decision Trees?

What are the advantages of logistic regression over decision trees? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand ...
The American Journal of Managed Care

Risk Classification of Medicare HMO Enrollee Cost Levels Using a Decision-Tree Approach

Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...
JSTOR Daily

Using classification and regression trees (CART) to support worker decision making

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful ...
International Monetary Fund

What is Really Good for Long-Term Growth? Lessons from a Binary Classification Tree (BCT) Approach

Although the economic growth literature has come a long way since the Solow-Swan model of the fifties, there is still considerable debate on the "real' or "deep" determinants of growth. This paper ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...