# Blog Archives

## Building the Data Matrix for the Task at Hand and Analyzing Jointly the Resulting Rows and Columns

June 6, 2016
By

Someone decided what data ought to go into the matrix. They placed the objects of interest in the rows and the features that differentiate among those objects into the columns. Decisions were made either to collect information or to store what was gath...

## Building the Data Matrix for the Task at Hand and Analyzing Jointly the Resulting Rows and Columns

June 6, 2016
By

Someone decided what data ought to go into the matrix. They placed the objects of interest in the rows and the features that differentiate among those objects into the columns. Decisions were made either to collect information or to store what was gath...

## Using Support Vector Machines as Flower Finders: Name that Iris!

May 25, 2016
By

Nature field guides are filled with pictures of plants and animals that teach us what to look for and how to name what we see. For example, a flower finder might display pictures of different iris species, such as the illustrations in the plot below. Y...

## Using Support Vector Machines as Flower Finders: Name that Iris!

May 25, 2016
By

Nature field guides are filled with pictures of plants and animals that teach us what to look for and how to name what we see. For example, a flower finder might display pictures of different iris species, such as the illustrations in the plot below. Y...

## The Kernel Trick in Support Vector Machines: Seeing Similarity in More Intricate Dimensions

May 24, 2016
By

The "kernel" is the seed or the essence at the heart or the core, and the kernel function measures distance from that center. In the following example from Wikipedia, the kernel is at the origin and the different curves illustrate alternative depiction...

## The Kernel Trick in Support Vector Machines: Seeing Similarity in More Intricate Dimensions

May 24, 2016
By

The "kernel" is the seed or the essence at the heart or the core, and the kernel function measures distance from that center. In the following example from Wikipedia, the kernel is at the origin and the different curves illustrate alternative depiction...

## The Mad Hatter Explains Support Vector Machines

May 9, 2016
By

"Hatter?" asked Alice, "Why are support vector machines so hard to understand?" Suddenly, before you can ask yourself why Alice is studying machine learning in the middle of the 19th century, the Hatter disappeared. "Where did he go?" thought Alice as ...

## The Mad Hatter Explains Support Vector Machines

May 9, 2016
By

"Hatter?" asked Alice, "Why are support vector machines so hard to understand?" Suddenly, before you can ask yourself why Alice is studying machine learning in the middle of the 19th century, the Hatter disappeared. "Where did he go?" thought Alice as ...

## When Choice Modeling Paradigms Collide: Features Presented versus Features Perceived

April 3, 2016
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What is the value of a product feature? Within a market-based paradigm, the answer is the difference between revenues with and without the feature. A product can be decomposed into its features, each feature can be assigned a monetary value by includin...

## When Choice Modeling Paradigms Collide: Features Presented versus Features Perceived

April 3, 2016
By

What is the value of a product feature? Within a market-based paradigm, the answer is the difference between revenues with and without the feature. A product can be decomposed into its features, each feature can be assigned a monetary value by includin...