Category Archives: Classification

Convolutional neural networks

Neural networks have been around for a number of decades now and have seen their ups and downs. Recently they’ve proved to be extremely powerful for image recognition problems. Or, rather, a particular type of neural network called a convolutional … Continue reading

Posted in Classification, Feature extraction | 3 Comments

Precision, Recall, AUCs and ROCs

I occasionally like to look at the ongoing Kaggle competitions to see what kind of data problems people are interested in (and the discussion boards are a good place to find out what techniques are popular.) Each competition includes a way … Continue reading

Posted in Classification | 3 Comments

Optimization

Optimization is a topic that has come up in a number of posts on this blog, but that I’ve never really addressed directly. So, I though it was about time that I gave it its own post. The term “optimization” … Continue reading

Posted in Classification, Regression | 3 Comments

Random forests

In last week’s post, I described a classification algorithm called a decision tree that defines a model/distribution for a data set by cutting the data space along vertical and horizontal hyperplanes (or lines in the two-dimensional example that we looked … Continue reading

Posted in Classification | 9 Comments

Decision Trees

In the last few posts, we explored how neural networks combine basic classification schemes with relatively simple distributions, such as logistic distributions with line/plane/hyperplane decision boundaries, into much more complex and flexible distributions. In the next few posts, I plan … Continue reading

Posted in Classification | 5 Comments

Neural Networks 3: Training

Note: I’ve started announcing new posts on twitter (@jejomath) for anyone who wants updates when new posts appear. In the last two posts, I described how a single neuron in a neural network encodes a single, usually simple, classifier algorithm, … Continue reading

Posted in Classification | 5 Comments

Neural Networks 2: Evaluation

In last week’s post, I introduced the Artificial Neural Network (ANN) algorithm by explaining how a single neuron in a neural network behaves. Essentially, we can think of a neuron as a classification algorithm with a number of inputs that … Continue reading

Posted in Classification | 12 Comments

Neural Networks 1: The neuron

In the next two posts, I plan to introduce the classification algorithm called an Artificial Neural Network (ANN). As the name suggests, this algorithm is meant to mimic the networks of neurons that make up our brains. ANNs are one … Continue reading

Posted in Classification | 20 Comments

Multi-class classification

If you paid really close attention to my last few posts, you might have noticed that I’ve been cheating slightly. (But if you didn’t notice, don’t worry – it was a subtle cheat.) When I introduced the problem of classification, … Continue reading

Posted in Classification | 12 Comments

Kernels

Over the last few weeks, I’ve introduced two classification methods – Support Vector Machines (SVM) and Logistic Regression – that attempt to find a line, plane or hyperplane (depending on the dimension) that separates two classes of data points. This has … Continue reading

Posted in Classification, Normalization/Kernels | 18 Comments