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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 outÂ 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 twodimensional 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
Multiclass 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) thatÂ separates two classes of data points. This has … Continue reading
Posted in Classification, Normalization/Kernels
18 Comments