Machine Learning.

What is Deep Learning?
14 August 2018 | by Jake Hoare
Deep learning is a subset of machine learning. Like other machine-learning techniques, deep learning creates a mapping from input data to a target outcome. After...

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How Random Forests Fit to Data
06 August 2018 | by Jake Hoare
A random forest is a collection of decision trees. The forest learns patterns in data and makes predictions based on those patterns. In this post,...

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tree on a hill
How is Splitting Decided for Decision Trees?
02 August 2018 | by Jake Hoare
Decision trees are a machine learning technique for making predictions. They are built by repeatedly splitting training data into smaller and smaller samples. This post...

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What is a Decision Tree?
01 August 2018 | by Jake Hoare
A decision tree makes predictions based on a series of questions. The outcome of each question determines which branch of the tree to follow. They...

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What is a Random Forest?
How is Variable Importance Calculated for a Random Forest?
30 July 2018 | by Jake Hoare
After training a random forest, it is natural to ask which variables have the most predictive power. Variables with high importance are drivers of the...

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Four Ways to Write Better Stan Code
12 July 2018 | by Mathew McLean
Writing Stan programs can be tricky so if you're already familiar with it - you're ahead of the curve. But maybe you want to find...

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What is a ROC Curve and How to Interpret It
05 July 2018 | by Carmen Chan

A Receiver Operator Characteristic (ROC) curve is a graphical plot used to show the diagnostic ability of binary classifiers. It was first used in signal…

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Predict Customer Churn with Gradient Boosting
03 July 2018 | by Jake Hoare
Customer churn is a key predictor of the long term success or failure of a business. But when it comes to all this data, what's...

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How to Export LDA Functions from Q into Excel
14 December 2017 | by Chris Facer

When using linear discriminant analysis (LDA) in market research, a common need is to obtain what are known as discriminant functions. These allow the analysis…

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Exporting LDA Functions from Displayr into Excel
08 December 2017 | by Jake Hoare

In this post I show how discriminant functions can be extracted from a Linear Discriminant Analysis in Displayr. Such functions are often used in Excel…

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Using Displayr
How to run Linear Discriminant Analysis in Displayr
17 October 2017 | by Jake Hoare
In this post I explain how to perform Linear Discriminant Analysis in Displayr. Linear Discriminant Analysis is a machine learning technique that can be used...

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Linear Discriminant Analysis in R: An Introduction
11 October 2017 | by Jake Hoare
How does Linear Discriminant Analysis (LDA) work and how do you use it in R? This post answers these questions and provides an introduction to...

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Machine Learning: Using t-SNE to Understand Middle Eastern Politics
06 October 2017 | by Tim Bock

The machine learning technique of t-SNE (t-distributed Stochastic Neighborhood Embedding) can summarize visualizations and extract additional insight from them. In this post, I illustrate this using a visualization…

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Machine learning pruning
Machine Learning: Pruning Decision Trees
04 July 2017 | by Jake Hoare
In machine learning and data mining, pruning is a technique associated with decision trees. Pruning reduces the size of decision trees by removing parts of...

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