knn algorithm

# # "Computer-born to keep up with the tide"Machine learning as a trend of development needs to be mastered by us now. Now I also need to start learn machine learning and record what I want to do here.Today I started my first lesson--k near algorithm . First, K-approaching basic concept understandingBefore learning begins, I will explain the idea of the K-nearest algorithm in the simplest words.K Nearest ne

I. The method of exhaustive Enumerate all the possibilities and go on to get the best results. As figure one, you need to go straight from point A to point G to know that F is the highest (best solution). The optimal solution obtained by this algorithm is certainly the best, but it is also the least efficient. Although the best solution can be obtained by exhaustive method, the efficiency is extremely low. In order to improve efficiency, you can not

KNN is one of the simplest classification methods. The idea of this method is: if most of the k most similar samples in the feature space (that is, the most adjacent samples in the feature space) belong to a certain category, the sample also belongs to this category. In KNN algorithm, the selected neighbors are objects that have been correctly classified. This me

Sort Categories sort by whether in memory Depending on whether the records to be sorted in the sort process are all placed in memory, the sort is divided into: inner and outer sort. For internal sorting, the performance of the sorting algorithm is mainly affected by 3 aspects:Time performance, auxiliary space, algorithmic complexity. according to the algorithm to achieve the complexity of classification S

the basic algorithm of data regression classification prediction and python ImplementAbout regression and classification of data and analysis of predictions. It is also considered as a relatively simple machine learning algorithm to discuss the algorithms for analyzing several comparative bases.A. KNN algorithmProximity algorithms, which can be used for regressi

1.3 scanning line Seed FillingAlgorithm The two seed filling algorithms described in sections 1.1 and 1.2 have the advantage of being very simple. The disadvantage is that recursive algorithms are used, which not only requires a large amount of stack space to store adjacent points, and the efficiency is not high. In order to reduce recursive calls in algorithms and reduce stack space usage, many improved algorithms are proposed, one of which is the scanning line Seed Filling

Reference: http://blog.csdn.net/hguisu/article/details/7996185more data mining algorithms :https://github.com/linyiqun/DataMiningAlgorithmLink AnalysisIn the link analysis there are 2 classic algorithms, one is the PageRank algorithm, and the other is the hits algorithm, plainly speaking, are doing link analysis. How to do it, continue to look down.PageRank algorithmTo talk about the function of the PageRan

Listen to a friend said machine learning is very cow, specially bought this "machine learning actual combat", learn computer learning, by the way to learn python.The first algorithm is KNN, easy to understand, simple and practical, but the complexity of storage and computation is a bit high, and can not give the intrinsic meaning of the data .The two examples introduced in the book Make Me feel that machine

Reprint please indicate source: http://www.cnblogs.com/tiaozistudy/p/twostep_cluster_algorithm.htmlThe two-step clustering algorithm is a kind of clustering algorithm used in SPSS Modeler, and it is an improved version of Birch hierarchical clustering algorithm. It can be applied to the clustering of mixed attribute datasets, and the mechanism of automatically de

Optimization Algorithm Starter series article catalog (in update):1. Simulated annealing algorithm2. Genetic algorithmsGenetic Algorithms (GA, Genetic algorithm), also known as evolutionary algorithms. Genetic algorithm is a heuristic search algorithm, which is inspired by Darwin's theory of evolution and used for refe

algorithms include K-nearest Neighbor (KNN), Learning vector quantization (learning vector quantization, LVQ), and self-organizing mapping algorithms (self-organizing map, SOM).Back to Top2.3 Regularization MethodThe regularization method is the extension of other algorithms (usually the regression algorithm), which adjusts the algorithm according to the complex

based on conditional probability and is inseparable from the prior probability and posterior probability of the observed sample.Summary: For classification, the probability of using something is more effective than using hard rules. Bayesian probabilities and Bayesian criteria provide an effective method for estimating unknown probabilities using known values. It is possible to reduce the need for data volume by assuming the conditional independence between features.Although the hypothesis of c

returned by this algorithm are accurate, but the time efficiency of this algorithm on high-dimensional datasets is not high. When the experiment [1] points out that the dimension is above 10, the time complexity of the algorithm based on space partition is less than the linear lookup. The LSH method can reduce the complexity of time and space under the premise o

Apriori is a algorithm for frequent item set Mining and association rule learning over transactional databases. It proceeds by identifying the frequent individual items on the database and extending them to larger and larger item sets As long as those item sets appear sufficiently often in the database. The frequent item sets determined by Apriori can is used to determine association rules which highlight general trends in The database:this have appli

Opengl implements line scanning algorithm and area filling algorithm, and opengl AlgorithmOverview 1. Use the line scanning algorithm to draw a line segment. A straight line consists of discrete points. 2. Use the area Filling Algorithm to draw a polygon area. The area consists of discrete points. Development Environme

Learn the reason for this algorithm: Yesterday afternoon stroll, met the girlfriend is looking at the algorithm, suddenly asked me will not Freud algorithm. I agreed to, and then spent half an hour to learn the algorithm, and 5 minutes to listen to her, and also to share with you in need of friends, so that you in the

1.3 Scanning line seed filling algorithm The advantages of the two seed filling algorithms described in sections 1.1 and 1.2 are very simple, with the disadvantage of using recursive algorithms, which not only require a lot of stack space to store adjacent points, but are inefficient. In order to reduce the recursive call in the algorithm and save the use of stack space, many improved algorithms are propos

K 1. Algorithm Description: 1.1 KNN KNN Two examples are provided to illustrate (1) The Green Circle is determined to be assigned to which class, is it a red triangle or a blue square? If ( Movie name Number of fights Number of kisses Movie type California Man 104 Romance He 2 100 Romance Beautif

Data Structure and Algorithm Analysis Study Notes (2)-algorithm analysis, data structure and algorithm analysis I. Simplest understanding and use of algorithm analysis methods 1. First, you may be confused by the mathematical concepts. In fact, simply put, it is assumed that the execution efficiency of any statement is

LeetcodeNine Chapters video Portal: HTTP://SINA.LT/EQC5live video lecture recordingNine ChaptersAlgorithmvideo recording, PPTalgorithm class, Algorithm intensive class,JavaBeginner and Basic algorithm class, Big Data Project actual combat class, Andriod project actual combat classChapter Nine algorithm downloadnine-Chapter al