Time: February 16, 2017 from 10am to 11am
Location: webinar: online and on-demand
Website or Map: http://hubs.ly/H069mgy0
Phone: (619) 543-8880 x109
Event Type: webinar
Organized By: Lisa Solomon
Latest Activity: Feb 8, 2017
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Webinar: Improve Your Regression with CART and Gradient Boosting
February 16th, 1PM – 2PM EST
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ABSTRACT:
In this webinar we'll introduce you to a powerful tree-based machine learning algorithm called gradient boosting. Gradient boosting often outperforms linear regression, Random Forests, and CART. Boosted trees automatically handle variable selection, variable interactions, nonlinear relationships, outliers, and missing values.
We'll see that CART decision trees are the foundation of gradient boosting and discuss some of the advantages of boosting versus a Random Forest. We will explore the gradient boosting algorithm and discuss the most important modeling parameters like the learning rate, number of terminal nodes, number of trees, loss functions, and more. We will demonstrate using an implementation of gradient boosting (TreeNet® Software) to fit the model and compare the performance to a linear regression model, a CART tree, and a Random Forest.
Who should attend:
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