I recently went through a Coursera course on Classification taught by Carlos Guestrin from U of Washington and thought it was excellent. There was an interesting discussion on model overfitting that I thought I would share. In previous posts I discussed linear models with shrinkage parameters such us ridge and lasso regression models. Similar approach … More Shaving a Classifier with Occam’s Razor
My posts have been spars as I adjust being back home. Today’s post will be about a somewhat gimmicky approach to visualizing correlation in the markets. A while back I came across an interesting article by Resovsky et al on minimum spanning trees. I do not have a background in graph theory but I have … More Minimum Spanning Trees
In today’s post I wanted to describe classification trees. I will concentrate on Classification and Regression Tree (CART) algorithm. As I discuss the main features of this algorithm I will contrast it with other widely used methods to construct classification trees. What A Classification Tree Looks Like: Before diving into the algorithm let’s have a … More Classification Trees
In my previous post I showed a coordinate descent algorithm for solving Lasso coefficients. Lasso model is part of a family of penalized regression models that are popular in machine learning and predictive modeling. In today’s post I want to show you how this model can be used to estimate the monthly average price of … More Lasso model example (LME’s Aluminium Futures Price)
Previously I discussed the benefit of using Ridge regression and showed how to implement it in Excel. In this post I want to present the LASSO model which stands for Least Absolute Shrinkage and Selection Operator. We are again trying to penalize the size of the coefficients just as we did with ridge regression but … More LASSO Regression in VBA
Haven’t had the time to add posts recently due to traveling plans but I’m back for a week and have sketched out a plan for a series of posts on predictive modeling. I recently received a fantastic bday present in the form of Applied Predictive Modeling by Max Kuhn and Kjell Johnson and highly recommended … More Ridge Regression in Excel/VBA
In this post I wanted to present a very popular clustering algorithm used in machine learning. The k-means algorithm is an unsupervised algorithm that allocates unlabeled data into a preselected number of K clusters. A stylized example is presented below to help with the exposition. Lets say we have 256 observations which are plotted below. … More K-Means Clustering in Excel
Today we wanted to add a short follow up on our previous post on artificial neural networks. The example which we gave of training an ANN on XOR function probably appears to be very trivial for the readers. Today we want to show another example that may highlight how neural networks can be used to … More Pattern Recognition with Neural Network in Excel (a toy example)
In this post we will discuss a popular class of neural networks, Artificial Feedforward Neural Network (ANN) which consists of input data, one or more hidden layers consisting of processing units and an output layer which returns the value of an estimated target value. An example of a processing unit is shown below. The processing … More Artificial Neural Network with Backpropagation Training in VBA
A very useful approach to analyzing price action of a particular security is to search historical instances where price exhibited similar behaviour. This type of analysis has often been called historical analogs by some writers. Below we will show a simple example that is easy to implement in excel. The aim is to select a … More Historical Analogs/ Time Series Clustering in Excel
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