Tag: classifier
How to program the Support Vector Machines algorithm
Support Vector Machine is one of the most commonly used supervised machine learning algorithms for data classification. A binary classifier, the support vector machine algorithm works in vector space to sort data points by finding the best hyperplane separating them into two groups. Thanks to its reliance upon vectors, it finds frontiers between groups of…
How to program the K Nearest Neighbors algorithm
K Nearest Neighbors is a popular classification algorithm for supervised machine learning. It permits to divide data points into groups, defining a model that will then be able to classify an unknown data point in one group or another. The K parameter, defined during programming, allows the algorithm to classify unknown data points by examining…
Programming a simple classifier with TensorFlow
TensorFlow is an open-source machine learning framework developed by Google. It relies upon Tensors (multi-dimensional arrays) which empower a wide range of API to develop machine learning applications, primarily deep neural networks. TensorFlow is commonly used in machine learning practice, so better start using it already. Thankfully the TensorFlow website provides a guide for programmers…
17. Learning: Boosting
“Wisdom of a weighted crowd of experts” Classifiers Classifiers are tests that produce binary choices about samples. They are considered strong classifiers if their error rate is close to 0, weak classifiers if their error rate is close to 0.5. By using multiple classifiers with different weights, data samples can be sorted or grouped according to different…