QA Official

Five Characteristics of Algorithm 2019-05-21
algorithm must be to solve a problem.It must be possible to solve the problem.Talking about algorithms is meaningless. algorithm's five characteristics: Input: The algorithm has 0 or more inputs Output: The algorithm has at least one or more outputs poor: the algorithm will end automatically after a limited number of steps without infinite loops, and each step can be completed within an acceptable time. Certainty: Each step in the algorithm has a definite meaning and there will be no ambiguity Feasibility: Each step of the algorithm is feasible, that is, each step can be executed a limited number of times.

JS——Mediator mode 2019-05-21
Let's make a simple analogy from our daily life. We go to a housing intermediary to rent a house. The housing intermediary forms an intermediary between the renter and the landlord lessor.The renter does not care whose house he rents.The landlord, the lessor, does not care who he rents.Because of the intermediary, this transaction has become so convenient. In the process of software development, it is bound to encounter such a situation that multiple classes or subsystems interact with each other, and the interaction is very complicated, resulting in each class must know the classes that it needs to interact with, so their coupling will appear unusually severe.

KNN algorithm matlab function 2019-05-21 build MDL = ClassificationKNN. FIT (x, y): Returns the classification model based on features and classification labels.X: Each row represents a feature vector, and each column represents a variable in the feature vector.Y: Each row represents the label or category represented by the feature vector theory in X.Mdl = (x, y, name, value): value represents the value of k. ClassificationKNN.predict: prediction label = predict (MDL, Xnew): xnew: to

KODI (software) (Original XBMC) Secondary Development Full Analysis (III)-Obtaining Video Input Stream 2019-05-21
The previous article talked about the establishment process of player. KODI (software) (formerly XBMC) secondary development fully analyzed (2)-Create player, and then the previous article determined which player is the real working player. m_pPlayer->CreatePlayer(newPlayer, *this);//Create player. The next article focuses on this and starts to create player. This m_pPlayer is an example of xbmc/ApplicationPlayer.h. H. The source code is as follows: void CApplicationPlayer::CreatePlayer(const std::string &player, IPlayerCallback& callback) { CSingleLock lock(m_player_lock);

ML Model 1: KNN Overview, Advantages and Disadvantages 2019-05-21
Introduction Given a supervised training set, for the new input instance, find the K instances nearest to the instance in the training set.If most of these K instances belong to a certain class, the input instance is divided into this class. Three Elements k value selection, distance measurement method and classification decision rules. k value selectionA small value of k (,means that the overall model is complex and may lead to over-fitting.

RF GBDT XGBOOST 2019-05-21
Gradient boosting(GB)The goal of learning algorithm in machine learning is to optimize or minimize loss Function. The idea of Gradient boosting is to iteratively generate multiple (M) weak models, and then add the prediction results of each weak model. The following model Fm+1(x) is generated based on the effect of Fm(x) of the previous learning model. Gradient boosting Decision Tree(GBDT)The most typical basic learner in GB algorithm is decision tree, especially CART.

iOS third party reads fingerprint 2019-05-21
third-party fingerprint reading must be above ios8 the necessary library # import < localauthentication/localauthentication. h > to import TouchId first. this library must be Xcode6 and connected to a real machine, so as not to prompt for errors that cannot be found, even if it is not iPhone5s.If it is a simulator, it will prompt that this library cannot be found. Then write the following code in a triggered event

matlab comes with examples of various classifiers 2019-05-21
what we know so far MATLABThe classifiers inare: KNeighbor Classifier, Random Forest Classifier, Naive Bayesian, Ensemble Learning Method, Discriminant Analysis Classifier, Support Vector Machine.The main functions are summarized as follows. For more details, please refer to MATLABHelp files.settraining samples: train_data %matrix, one sample per row and one feature per columnTraining Sample Label: train_labelAlfred Hitchcock Presents" The Percentagecolumn vectorTest Sample: test_dataTest Sample Label: test_label KNeighbor Classifier ( KNN ) mdl =

python Access Baidu AI Face Recognition Crawler to Obtain Beautiful Woman Pictures and Score (Source Code Attached) 2019-05-21
python Access Baidu AI Face Recognition Crawler to Obtain Beauty Pictures and Score Project Download Address: 1 Data Source Pictures Appearing in Answers to All Questions under Zhihu Topic "Beauty" 2 Grab Tool Python Here, I would like to recommend my own Python development learning group: 483546416, which is all developed by learning Python. If you are learning Python, you are welcome to join the small compilation.

Algorithm and Data Structure-Select Sort 2019-05-21
Algorithm and Data Structure-Select Sort algorithm idea For example, given an unordered array int arr={1,3,2,6,9};N represents the length of the set array, and an algorithm is given to arrange the array arr from small to large. Select sorting: traverse [i,n] to find the minimum value, exchange with the position of I after finding it, and so on. code public static void selectionSort(int[] arr,int n){ for(int i=0;i<n;i++){ int min