Table of Contents 1. Data and analysis objects 2. Purpose and analysis tasks 3. Methods and Tools 4. Data reading 5. Data understanding 6. Data preparation 7. Model training 8. Model evaluation 9. Model parameter adjustment 10. Model improvement 11. Model prediction 1. Data and analysis objects CSV file – “bc_data.csv” Dataset link: https://download.csdn.net/download/m0_70452407/88524905 This […]
Tag: knn
Find pr curve and roc curve based on knn algorithm
Table of Contents 1. Basic principles of knn algorithm 2. What is PR curve? 3. Drawing of pr curve 4.What is ROC curve? 5.Drawing of roc curve 6. Realize drawing pr curve and roc curve pr curve python implementation code: roc implementation code: 1. Basic principles of knn algorithm The knn algorithm is also called […]
KNN algorithm c++ implementation
Source [Machine Learning Practice One]: C++ implements K-nearest neighbor algorithm KNN_The feature vectors of two images are matched using the knn model – CSDN Blog k-Nearest Neighbor (kNN, k-NearestNeighbor) selects the k neighbors closest to the input data point in the training set, and uses the category with the most occurrences among the k neighbors […]
Encapsulate the KNN classifier into a complete and usable simple system
In this system, you define a number of functions, including: classify0: implements the classifier of the KNN algorithm. file2matrix: Used to open and parse files, converting data into feature matrices and corresponding classification labels. autoNorm: Normalize the feature matrix to ensure that the numerical ranges of different features are similar. classifyPerson: Allows users to input […]
Use KNN algorithm to draw PR curve and ROC curve
In the evaluation of machine learning algorithms, especially in the evaluation of classification algorithms, the concepts of overfitting, underfitting, precision and recall, ROC curve and PR curve are used. Table of Contents 1. Basic parameters 2. Concept PR curve precision and recall PR curve drawing ROC curve TPR and FPR ROC curve drawing 3. Code […]
K-nearest Neighbors Algorithm (KNN, K-nearest Neighbors Algorithm)
Article directory Preface Application scenarios Euclidean distance (Euclidean distance) Two categories, single attribute (1D) Two categories, two attributes (2D) Two types, two or more attributes (>3D) Examples in R another one Please add what is a variable What are variables? What are numerical and categorical variables? Foreword I saw an article before, and the K […]
[RKNN] In YOLO V5, the output of pytorch2onnx, pytorch and onnx models is inconsistent and the accuracy is reduced.
After converting the model trained on yolo v5 to onnx and then to rknn, the test found: rknn model, both quantified and non-quantified, has lower test accuracy than the pytorch model. onnx model, compared to the pytorch model, the test accuracy is also reduced, and is closer to the accuracy of the rknn model Therefore, […]
K nearest neighbor (KNN) algorithm
Table of Contents K nearest neighbor (KNN) algorithm I. Overview 2. Basic principles 3. Distance indicators commonly used in KNN algorithm 4. Advantages and disadvantages of KNN algorithm 5. General process of K nearest neighbor algorithm 6. Algorithm implementation 7. Summary K Nearest Neighbor (KNN) algorithm 1. Overview The K-nearest neighbor (KNN) algorithm is a […]
Simple classification experiment based on KNN
Table of Contents 1. Brief introduction to K neighbor algorithm 2.Knn algorithm principle 3. Mail classification example based on knn 1. Brief introduction to K neighbor algorithm K-Nearest Neighbors (KNN for short) is a statistical method used for classification and regression. KNN can be said to be one of the simplest classification algorithms, and at […]
k-nearest neighbor algorithm (kNN algorithm)
Table of Contents 1. Understanding the k-nearest neighbor algorithm 1 Overview 2.Principle 3.Distance indicators commonly used in kNN algorithm (1) Euclidean Distance (2) Manhattan Distance 2. General process of kNN algorithm 1. Data preparation Normalized 2. Select distance measurement method 3. Determine the k value and find the k nearest neighbors 4. Prediction 3. kNN […]