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KNN, namely k-nearest neighbor method, is a basic classification and regression method proposed by Cover T and Hart P in 1967. It is also one of the basic algorithms of machine learning. This article's reference tutorial: Machine learning practice Principle of KNN algorithm In a sample data set, also known as the training sample set, and eac ...

      Since the development of computer algorithms, there have been many different classifications. At present, the most widely used is the generalized swarm intelligent optimization algorithm. For example, particle swarm optimization (PSO), whale optimization (WOA), gray wolf optimization (GWO), dragonfly optimization (DA), uni ...

Data Attribute information: 1) ID number 2) Diagnosis (M = malignant, B = benign) Calculate 10 real value characteristics of each nucleus: a) Radius (average distance from center to perimeter) b) Texture (standard deviation of gray value) c) Perimeter d) Area e) Smoothness (local variation of radius length) f) Compactness (perimeter ^ ...

Data description Data parameters OrderNumber: customer nickname LineNumber: purchase order. For example, the first three lines respectively represent three goods purchased by the same customer Model: trade name Problem description Application of intelligent algorithm recommendation of association rules based on shopping basket. Three basic ...

Atomization treatment can be represented by the following model: I (x): foggy picture J (x): picture of defogging     A :     Global atmospheric light T (x): intermediate transformation mapping, depending on unknown depth information, medium transmission map       The previous defogging methods used r ...

Original link: http://tecdat.cn/?p=24498In this example, we consider Markov transformation stochastic volatility model.statistical modelGive Way    Are dependent variables and    Unobserved log volatility  The stochastic volatility model is defined as follows  Zone variable    Following a two-state Markov ...

review Ben delayed his sophomore electrical settings, and was lucky to join the team halfway. The author had not done camera and visual code before (AI electromagnetic), although there were various regrets in the end, but also temporarily learned a lot of new knowledge. Before the assessment, the foundation and development were completed s ...

I. Preface For guaranteed customer group, how to conduct detailed analysis and mining on the guaranteed customer group type? As shown in Figure 1, how do I get the label and how do I label it? Figure 1: Sample Diagram Using graph technology, you can label the triangle directly. Algorithmic steps Guarantee association data cleaning; ...

preface Bayesian classifier is a probability model, which uses Bayesian formula to solve the classification problem. Assuming that the feature vector of the sample obeys a certain probability distribution, we can calculate the conditional probability that the feature vector belongs to each class. The classification result is the one with the l ...

PPASR streaming and non streaming speech recognition The project will be divided into three stages: beginner ,Progressive class and Final stage Branch, which is currently the final level and continuously maintains the version. PPASR Chinese name PaddlePaddle Chinese speech recognition (PaddlePaddle Automatic Speech Recognition), is a PaddlePa ...