ai learning algorithms

"Merge Sort" Here we use recursive algorithm to keep the list in two, base case is no element in the list or only one element, because this sub-list is bound to be a positive sequence, and then gradually merge the two sorted sub-list into a new positive sequence table, until all the elements sorted."This is a process from the bottom up (bottom-up)Divides the list from the middle into two sub-lists until it reaches the bottom, with only one element in the sub-list　　Then, the two sub-lists are mer

size of the Eden area and the scale of the Survivior area-XX:+USEPARNEWGC:Using the parallel collector in the Cenozoic-XX:+USEPARALLELGC:The new generation uses the parallel collection collector-XX:+USEPARALLELOLDGC:Old age using the parallel collection collector-XX:+USESERIALGC:Using the serial collector in the new generation and the old age-XX:+USECONCMARKSWEEPGC:New generation uses parallel collectors, older generations using cms+ serial collectors-xx:+usecmscompactatfullcollection:Sets whet

Nine algorithms for machine learning---naive Bayesian classifierTo understand the Naive Bayes classificationBayesian classification is a generic term for a class of classification algorithms, which are based on Bayesian theorem, so collectively referred to as Bayesian classification. Naive naive Bayesian classification is the simplest and most common classificati

An ACM If the course, taking advantage of the ACM off-season, began to learn the introduction of the algorithm, after a year of ACM learning, gradually discovered, learn something, in-depth is the king, before learning an algorithm, always read the beginning to do the problem, until later found a lot of topics, will algorithm, but do not know is using this algorithm, This is the result of the algorithm unde

classes more equal. but .....Recall, though,that better data often beats better algorithms, and designing good features goes a long. And if you had a huge dataset, your choice of classification algorithm might not really matter so much in terms of Classi Fication performance (so choose your algorithm based on speed or ease of use instead).And if you really-accuracy, you should definitely try a bunch of different classifiers and select the best one by

SAS graphical user interfaces help you build machine-learning models and implement an iterative machine learning process. You don ' t have a advanced statistician. Our comprehensive selection of the machine learning algorithms can help you quickly get the value from your big data. They include: Neural networks

Today, I met a friend on the Internet who had been absent from QQ for a long time. He graduated from a computer science department from a Nanjing University. He asked me a question as soon as he got up. He said that he has been studying Computer for four years. In the end, I don't know what I learned. A teacher takes a computer class as a math class. Then he listed the questions that many teachers gave when they went to C. Such as a series. Helen's formula. He said that he was too big. He recent

Introduction to Learning sorting algorithmsLearning sequencing (learning to Rank, LTR) is a sort of algorithm based on machine learning method.Traditional classical models, such as the VSM model based on the TFIDF feature, are difficult to incorporate into many features, that is, in addition to the TFIDF features, they cannot be incorporated into other types of f

, Bellman-ford, maximum flow, binary matching and so on. It should be easy for people who are familiar with ACM.5. Problems in the design of computer algorithms:The algorithm design includes: Dynamic programming, backtracking search, divide and conquer, branch and bound method (solving integer solution) and so on.6. Three non-classical algorithms for Optimization theory:A) Simulated annealing method (SA)b) Neural Network (NN)c) Genetic algorithm (GA)I

KNN algorithm of ten Algorithms for machine learningThe previous period of time has been engaged in tkinter, machine learning wasted a while. Now want to re-write one, found a lot of problems, but eventually solved. We hope to make progress together with you.Gossip less, get to the point.KNN algorithm, also called nearest neighbor algorithm, is a classification algorithm.The basic idea of the algorithm: Ass

In this paper, Python implements the following four kinds of insert sort, cardinal sort, hill sort, bubble sort, high speed sort, direct selection sort, heap sort, merge sort.Previous: Python Learning (iii) Implementation of eight sorting algorithms (Part One)1. High-speed sequencingDescriptive narrativeBy sequencing the data to be sorted into separate two parts, one part of the whole data is smaller than t

Today, we learned the algorithm of merging and sorting on the introduction of algorithms, and finished writing pseudo-code on the paper, before learning to merge but not understanding thoroughly, in Before also has been puzzled: why clearly merge sort than the time complexity of the fast row more stable, why the library function does not merge and use the Fast row, now know the reason, because the merg

becomes the mean vector μ (mean vector) and the covariance matrix σ (Convariance matrix) .PART1.2.1 GDA ModelIn the GDA model, we modeled P (x|y) with a multivariate normal distribution:, i.e.Or the same as the original analysis method, the maximum likelihood-----log----to find the extremum. Finally have toNotice the meaning of some symbols in this area:Indicates that all of the X (i) and "1" of the classification result is 0, which can be understood as a indicator function, the expression in c

Learning algorithm or suggest a look at the algorithm introductionIntroduction to the third edition of the algorithm if you do not see the mathematical deduction only to see the pseudo-code difficulty or moderateThis series is just a process of documenting my learning experience and pseudo-code conversion codeIn-depth learning is also recommended to look at Algor

A simple introduction to machine learning algorithms.As the team (Big Data Team) technology development needs, through the traffic business data needs to expand, to achieve data mining and data analysis technology mastery, bypassing the machine learning algorithm, it can be said that the core value of big data lies in the algorithm.For example, the current machine learn