choosing machine learning classifier

you. In addition to the algorithms, AML integrates packages that 400+ multiple R languages.The choice of the algorithm, whether for beginners or experienced data scientists, in fact, is a very cost-minded thing. Microsoft also provides a lot of information to help you decide which algorithms to choose. Here are a few very useful links (in English):Microsoft Azure Machine learning algorithm Cheat sheet-http

Machine Learning 4, machine learning Probability-based classification method: Naive BayesBayesian decision theory Naive Bayes is a part of Bayesian decision-making theory. Therefore, before explaining Naive Bayes, let's take a quick look at Bayesian decision-making theory knowledge. The core idea of Bayesian decision-m

deep understanding of machine learning: Learning Notes from principles to algorithms-1th week 02 easy to get started Deep understanding of machine learning from principle to algorithmic learning notes-1th week 02 Easy to get star

Original: http://blog.csdn.net/abcjennifer/article/details/7834256This column (machine learning) includes linear regression with single parameters, linear regression with multiple parameters, Octave Tutorial, Logistic Regression, regularization, neural network, design of the computer learning system, SVM (Support vector machines), clustering, dimensionality reduc

Original: Image classification in 5 Methodshttps://medium.com/towards-data-science/image-classification-in-5-methods-83742aeb3645 Image classification, as the name suggests, is an input image, output to the image content classification of the problem. It is the core of computer vision, which is widely used in practice. The traditional method of image classification is feature description and detection, such traditional methods may be effective for some simple image classification, but the tradit

What is integrated learning, in a word, heads the top of Zhuge Liang. In the performance of classification, multiple weak classifier combinations become strong classifiers. In a word, it is assumed that there are some differences between the weak classifiers (such as different algorithms, or different parameters of the same algorithm), which results in different classification decision boundaries, which me

Regression classificationDecision Tree(CART) Classification Tree Fitctree Training classification Binary Decision tree Regression tree Fitrtree Training regression Binary Decision tree SupportVector machine Two-class support vector machine Fitcsvm Training two classification support vector

Interactive gradual regression Generalized linear regression with regularization Lassoglm Generalized linear regression using the regularization of elastic networks Regression classificationDecision Tree(CART) Classification Tree Fitctree Two-fork decision tree for training classification Regression tree Fitrtree Training regression two-fork decision Tree SupportVector machine