aml machine learning

discriminant models (discriminative model)The generation method is obtained by the data Learning Joint probability distribution P (x, y) and then the conditional probability distribution P (y| X) as the predictive model, the model is generated : P (Y |X )= P(X,Y)p ( X ) This method is called a build method , which represents the generation relationship of output y produced by a given input x. such as: Naive Bayesian and Hidden M

steepness factor to these nonlinear functions, adjust the saturation region of the nonlinear function, adjust the shape of the training loss function, and adjust the parameter adjustment out of the saturated area.For the sigmoid function, the steepness factor (recorded as λ) can be set as follows: Δs (x) =1/(1+exp (-x/λ))2.1.4 Using numerical optimization techniquesIn order to improve the convergence speed and stability of neural network training, we can also use the numerical optimization algo

I hear that Hulu machine learning is better than a winter weekend.You can click "Machine Learning" in the menu bar to review all the previous installments of this series and comment on your thoughts and comments.At the same time, in order to make everyone better understand Hulu, the menu "about Hulu" also made the corr

This series of blogs records the Stanford University Open Class-Learning notes for machine learning courses.Machine learning DefinitionArthur Samuel (1959): Field of study that gives computers the ability to learn without being explicitly programmed.Tom Mitchell (1998): A computer program was said to learn from experie

In recent years, with the rise of big data, cloud computing, mobile Internet, artificial intelligence technology, "machine learning" has become a hot term in the industry. From the field of communication Internet experts, to a variety of enterprises, and even ordinary people, the "machine learning" technology knows. So

Reprinted please indicate Source Address: http://www.cnblogs.com/xbinworld/archive/2013/04/21/3034300.html Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of

Original writing. For more information, see http://blog.csdn.net/xbinworld,bincolumns. Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of research on

Draw a map, there is the wrong place to welcome correct:In machine learning, features are critical. These include the extraction of features and the selection of features. They are two ways of descending dimension, but they are different:feature extraction (Feature Extraction): creatting A subset of new features by combinations of the exsiting features. In other words, after the feature extraction A feature

Original: Image classification in 5 MethodsAuthor: Shiyu MouTranslation: He Bing Center 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 traditional classification method is overwhelmed