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Anatomy of Decision Trees using an example from Kaggle
Submitted by Saurabh Banerjee (@saurabhbanerjee) on Monday, 15 June 2015
Section: Full Talk Technical level: Intermediate
Decision trees are amongst the most popular predictive modelling techniques in the analytics industry. Attendees will learn how to effectively apply decision trees to predict survival on the Titanic: Machine Learning from Disaster problem in Kaggle.
Attendees will learn about practical considerations for predictive modelling using Decision Trees, Bagging, Boosting, Random Forest using a simple example from Kaggle. The session will include slide presentation accompanied with demonstration using R and Rapidminer. Participants should be familiar with basics of predictive analytics including classification.
Attendees would not need to bring anything.
Saurabh is a Senior Specialist at Sapient Global Markets. He has 20 years of industry experience in technology consulting and product development in USA and India. Saurabh’s domain experience includes Financial Services, Healthcare and Telecom. In his current role, he is responsible for driving sales, delivery and innovation efforts in Data Analytics space at Sapient Global Markets.
Prior to Sapient, Saurabh worked with PwC as Associate Director, Strategy & Architecture practice. He is passionate about machine learning and understanding its impact on businesses, world economy and future generations.