ai learning algorithms

threshold of the class, and it is saved for clustering. This method of finding EPs mainly takes into account that data sets of different densities should be based on the density of each data. The appropriate thresholds were selected for clustering. Because the parameters used in clustering can only determine the density difference in the same class of data in the cluster results, the error caused by the parameter selection will not have a great effect on the clustering result.2.2 DBSCAN cluster

This paper mainly includes the realization of common machine learning algorithms, in which the mathematical derivation, principle and parallel implementation will give the link. Machine Learning (machines learning, ML) is a multidisciplinary interdisciplinary subject involving probability theory, statisti

classification method is used to solve the nonlinear problem in two steps, first using a transform to map the data of the original space to the new space, and then using the line-line classification learning method in the new space.Learn the classification model from the training data.If a kernel function is semi-positive, it is valid.In order to solve the problem of outliers, penalties are introduced. The new model should not only make the interval

[x] * w + interaction# calculate the predicted output loss = Sigmoid (classlabels[x] * p[0, 0])-1 Print loss w_0 = W_0-alpha * loss * Classlabels[x] for i in Xrange (n): If datamatrix[x, I]! = 0:w[i, 0] = w[i, 0]-alpha * loss * classlabels[x] * datamatrix[x, I] for j in Xrange (k): V[i, j] = V[i, j]-alpha * loss * CLASSLABELS[X] * (data Matrix[x, i] * inter_1[0, J]-V[i, j] * datamatrix[x, i] * datamatrix[x, I]) return w_0, W, Vdef Getaccura Cy (Datamatrix, Classlabels, W_0, W, v):

intersection of segments, the multi-angular area formula.8. Call the system qsort, a lot of tricks, slowly mastered.9. Conversion between any binaryPhase II:Practice a bit more complex, but also more commonly used algorithms.Such as:1. Two graph matching (Hungary), Minimum path overlay2. Network flow, minimum cost flow.3. Segment tree.4. And check the set.5. Familiar with the various models of dynamic programming: LCS, maximum increment substring, triangulation, memory DP6. Game-like

Machines (SVM), referred to as the SV Machine (the general abbreviation in the paper). It is a supervised learning method, which is widely used in statistical classification and regression analysis. Support Vector machines map vectors to a higher dimensional space, where a maximum interval of hyperspace is established in this space. On both sides of the super plane that separates the data, there are two super-planes that are parallel to each other. T

the depth of decision tree(2) The structure of the tree changes due to a little change in the sample, which can be improved by integrated learning.Application:(1) Financial options for option pricing are of great use(2) Remote sensing is the application field of pattern recognition based on decision Tree(3) Banks use decision tree algorithm to classify the probability of default payment by loan applicant(4)Gerber Products Inc., a popular baby products company, uses decision tree machine

Analysis of malware through machine learning: Basic Principles of clustering algorithms in Deepviz Since last year, we have discovered that many audiovisual companies have begun to engage in machine learning and artificial intelligence, hoping to find a fast and effective way to analyze and isolate new types of malware and expand the malicious software library. H

, activating the back of the nerve layer, the final output layer of the nodes on the node on behalf of a variety of fractions, example to get the classification result of Class 1The same input is transferred to different nodes and the results are different because the respective nodes have different weights and biasThis is forward propagation.10. MarkovVideoMarkov Chains is made up of state and transitionsChestnuts, according to the phrase ' The quick brown fox jumps over the lazy dog ', to get

conjugate gradient method is not only one of the most useful methods to solve the large scale linear equations,is also one of the most effective algorithms for solving large-scale nonlinear optimization. In various optimization algorithms, the conjugate gradient method is very important. Its advantage is that the required storage capacity is small, has step convergence, high stability, and does not require

Self-study machine learning three months, exposure to a variety of algorithms, but many know its why, so want to learn from the past to do a summary, the series of articles will not have too much algorithm derivation.We know that the earlier classification model-Perceptron (1957) is a linear classification model of class Two classification, and is the basis of later neural networks and support vector machin

of the total number of features with non-0 weights)9. Logistic regression : Two-dollar category, extremely efficient Giallo Computer System (many problems need to use probability estimates as output) two ways: "As is" "converted to two-dollar category" Application: Automatic diagnosis of disease (to investigate the risk factors that cause disease, and to predict the probability of disease occurrence according to risk factors), economic forecasts and other fieldsCategory: Evaluation indicators:

specific job requirements, image algorithm For example, now deep learning hot not I said, so the basic convolution neural network algorithm , image classification , image detection The more famous paper in recent years should read it. If you have a condition, use it like a caffe,tensorflow frame.2. Machine Learning EngineerThis post is basically the same as the algorithm, and mainly serves the internal bus

machine Learning Algorithms Summary 1. Preface by using the machine learning algorithm to summarize the work, convenient for later search, rapid application. 2. Recommended Algorithms Cross Minimum Variance algorithm name Cross minimum variance, alternating Leas

For the following three reasons, we chose python as the programming language for implementing machine learning algorithms: (1) Clear Python syntax; (2) Easy to operate plain text files; (3) widely used, there are a large number of development documents. Executable pseudocode Python has a clear syntax structure and is also called executable pseudo-code ). The default Python development environment has many a

)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

,elemtype e){int j,k,l;K = max_size-1;if (i{return ERROR;}j = malloc_sll (L);//Call the function written above,if (j){L[j].data = e;for (l=1;l{K = L[k].cur;}L[j].cur = L[k].cur;L[k].cur = j;return OK;}return ERROR;}Delete operation650) this.width=650; "title=" 11.jpg "src=" http://s3.51cto.com/wyfs02/M02/57/28/wKioL1STg1TTn7fqAAHvw03C2fQ503.jpg "alt=" Wkiol1stg1ttn7fqaahvw03c2fq503.jpg "/>Sample codeStatus Listinsert (staticlinklist l,int i){int j,k;K = max_size-1;if (i{return ERROR;}j = malloc_

can be processed.Cons: Easy to fit.How to avoid overfitting:(1) dimensionality reduction, can use PCA algorithm to reduce the dimension of the sample, so that the number of theta of the model is reduced, the number of times will be reduced, to avoid overfitting;(2) regularization, the design of regular items regularization term.The regularization function is to prevent some properties before the coefficient weight is too large, there has been a fitting.Note that the way to resolve overfitting i

Stack1stack-EMPTY (S)2 iftop[s]=03ThenreturnTRUE4 Else returnFALSE5 6 PUSH (s,x)7top[s]←top[s]+18 s[top[s]]←x9 Ten POP (S) One ifstack-EMPTY (S) AThen error"underflow" - Elsetop[s]←top[s]-1 - returns[top[s]+1]Queue1 ENQUEUE (q,x)2 q[tail[q]]←x3 iftail[q]=Length[q]4Then tail[q]←15 Elsetail[q]←tail[q]+16 7 DEQUEUE (Q)8 X←q[head[q]]9 ifhead[q]=Length[q]TenThen head[q]←1 One Elsehead[q]←head[q]+1 A returnXLinked list1list-SEARCH (l,k)2 X←head[l]3 whileX!=nil and key[x]!=k4

Encryption type and its related algorithmsAs the internet becomes more and more intense, attacks on the internet are on the rise, so the information passed on the Internet is increasingly unsafe, so in order to prevent users from stealing data that is transmitted over the Internet, we have to strengthen the security of the data being transmitted.The security of data mainly includes the following three aspects:Confidentiality of data: guaranteed data not to be readTo make the passed data unreadab