# Tag: CART (10)

**Random Forests®, Explained**- Oct 17, 2017.

Random Forest, one of the most popular and powerful ensemble method used today in Machine Learning. This post is an introduction to such algorithm and provides a brief overview of its inner workings.**Learn How to Make Machine Learning Work (webinars every Tue in October, Live or on-demand)**- Sep 28, 2017.

To fully use machine learning, we first need to understand both the potential benefits and the techniques to create data-driven models. In this webinar series, we will show you how to easily and automatically apply complex algorithms to data in real world applications.**Webinar: Improve Your CLASSIFICATION with CART(r) and RandomForests(r), Mar 29**- Mar 27, 2017.

We discuss the advantages of tree based techniques, including automatic variable selection, variable interactions, nonlinear relationships, outliers, and missing values.**Webinar: Improve Your Regression with CART and Gradient Boosting, Feb 16**- Feb 13, 2017.

Learn about a powerful tree-based machine learning algorithm called gradient boosting, which often outperforms linear regression, Random Forests, and CART.**Decision Tree Classifiers: A Concise Technical Overview**- Nov 3, 2016.

The decision tree is one of the oldest and most intuitive classification algorithms in existence. This post provides a straightforward technical overview of this brand of classifiers.**Webinar: Tips & Tricks for Customer Segmentation, July 21**- Jul 10, 2015.

We show customer segmentation of a German banking database, using different attributes to identify segments likely to be good credit risks. We will use CART and other algorithms like gradient boosting.**Top 10 Data Mining Algorithms, Explained**- May 21, 2015.

Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.**Comprehensive Data Science Training by Salford Systems, Dec 3-5, Online or San Diego**- Nov 4, 2014.

Learn the basics tree-structured data mining with CART, and progress to more advanced topics including Linear, Logistic, Nonlinear, Regularized, Lasso, MARS, TreeNet (Stochastic Gradient Boosting) and RandomForests(r), including Latest Refinements and Model Compression.**Salford Comprehensive Data Science Training, Dec 3-5, San Diego or Online**- Oct 21, 2014.

Learn the basics tree-structured data mining with CART, and progress to more advanced topics including Linear, Logistic, Nonlinear, Regularized, Lasso, MARS, TreeNet (Stochastic Gradient Boosting) and RandomForests(r), including Latest Refinements and Model Compression.**Data Mining for Beginners Boot Camp, Salford video series**- Jan 29, 2014.

This series shows how to easily apply SPM software suite to your predictive modeling projects, using a modern banking application as an example. This series is at the beginner level, and is perfect for first-time users or for those who need a refresher course in model building and data analysis.