A Short Introduction: Boosting and AdaBoost
Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers. This is done by building a model from the training data, …
Category: algorithms
A Short Introduction: Bagging and Random Forest
Random Forest is one of the most popular and most powerful machine learning algorithms. It is a type of ensemble machine learning algorithm called Bootstrap Aggregation or bagging. The …
A Short Introduction: Support Vector Machines
Support Vector Machines are perhaps one of the most popular and talked about machine learning algorithms. A hyperplane is a line that splits the input variable space. In Support …
A Short Introduction to Learning Vector Quantization
A downside of K-Nearest Neighbors is that you need to hang on to your entire training dataset. The Learning Vector Quantization algorithm (or LVQ for short) is an artificial …
A Short Introduction to K-Nearest Neighbors Algorithm
The KNN algorithm is very simple and very effective. The model representation for K-Nearest Neighbors Algorithm is the entire training dataset. Simple right? Predictions are made for a new …