Algorithms

previous article, we introduced the core mechanism of Gradient Boosting through Gradient Boosted Linear Regression. That example was deliberately easy. Its goal was not performance, but understanding. Using a linear model allowed us to make...

Neural Network Regressor, we now move to the classifier version. From a mathematical viewpoint, the 2 models are very similar. In truth, they differ mainly by the interpretation of the output and the selection...

article about SVM, the subsequent natural step is Kernel SVM. At first sight, it looks like a very different model. The training happens within the dual form, we stop talking a few slope and...

we're. That is the model that motivated me, from the very starting, to make use of Excel to raised understand Machine Learning. And today, you'll see a different explanation of SVM than you normally see,...

of my Machine Learning “Advent Calendar”. I would really like to thanks on your support. I even have been constructing these Google Sheet files for years. They evolved little by little. But when it's...

, we explored how a Decision Tree Regressor chooses its optimal split by minimizing the Mean Squared Error (MSE). Today for Day 7 of the Machine Learning “Advent Calendar”, we proceed the identical approach but...

working with k-NN (k-NN regressor and k-NN classifier), we all know that the k-NN approach could be very naive. It keeps your entire training dataset in memory, relies on raw distances, and doesn't...

5 days of this Machine Learning “Advent Calendar”, we explored 5 models (or algorithms) which are all based on distances (local Euclidean distance, or global Mahalanobis distance). So it's time to change the approach,...