most common machine learning algorithms

Original: http://dataunion.org/13451.htmlXbinworld Introduction:In the field of machine learning, the so-called dimensionality reduction refers to the mapping of data points in the original high-dimensional space to the low-dimensional space. The essence of dimensionality is to learn a mapping function f:x->y, where x is the expression of the original data point, which is currently used at most in vector re

Ten classic algorithms in machine learning and Data Mining Background: In the early stage of the top 10 algorithm, Professor Wu made a report on the top 10 challenges of Data Mining in Hong Kong. After the meeting, a mainland professor put forward a similar idea. Professor Wu felt very good and began to solve the problem. I found a series of big cows (both big co

, root search algorithms are used in mainstream programming languages to determine whether an object is alive. The idea of this algorithm is to start from a series of "GC roots" objects as the starting point and start to search downward. The path searched through becomes "reference chain ", when there is no reference link between an object and GC roots, this object cannot be reached. For example, if object 5, 6, and 7 do not have a reference chain of

Roundtable", most of the real-life data is "living" in "high-dimensional space", and the simpler it is to deal with high-dimensional data, the more practical it is. With international academics like Martin introducing algorithms such as statistical machine learning to China, it is expected to accelerate the challenge of solving China's big data phenomena with ar

I. The idea of integrated learning methodThis paper introduces a series of algorithms, each of which has different scopes of application, such as dealing with linear variational problems, and dealing with linear irreducible problems. In the real world life, often because the "collective wisdom" makes the problem is easy to solve, then the problem, in machine

)Feature Selection (Feature selection algorithm):Mutual information (Mutual information), Documentfrequence (document frequency), information Gain (information gain), chi-squared test (Chi-square test), Gini (Gini coefficient).Outlier Detection (anomaly detection algorithm):Statistic-based (based on statistics), distance-based (distance based), density-based (based on density), clustering-based (based on clustering).Learning to Rank (based on

Internationally authoritative academic organization the IEEE International Conference on Data Mining (ICDM) selected ten classic algorithms for data Mining in December 2006: C4.5, K-means, SVM, Apriori, EM , PageRank, AdaBoost, KNN, Naive Bayes, and CART.Not only the top ten algorithms selected, in fact, participate in the selection of the 18 algorithms, in fact,

Algorithms have become an important part of our daily lives, and they almost appear in any area of business. Gartner, the research firm, says the phenomenon is "algorithmic commerce", where algorithmic commerce is changing the way we operate and manage companies. Now you can buy these various algorithms for each business area on the "algorithmic market". The algorithmic market provides developers with more

, here is introduced 1vs (n–1) and 1v1. More SVM Multi-classification application introduction, reference ' SVM Multi-Class classification method 'In the previous method we need to train n classifiers, and the first classifier is to determine whether the new data belongs to the classification I or to its complement (except for the N-1 classification of i). The latter way we need to train N * (n–1)/2 classifiers, the classifier (I,J) is able to determine whether a point belongs to I or J, and whe