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Introduction ¶ In this experiment, we will implement the principal component analysis method and use it to obtain the low dimensional representation of face image. The data sets used in this experiment include: ex4data1.mat -2D simulation dataset ex4data2.mat -LFW face dataset The scoring criteria are as follows: Key point 1: realize PC ...

View the contents of the main function and read the file first if __name__ == '__main__': #data_extract_json = /home/xiaoguzai / code / French research cup text summary / datasets/train_extract.json data = load_data(data_extract_json) data_x = np.load(data_extract_npy) data_seq2seq_json = data_json[:-5] + '_seq2seq.json' co ...

  Introduction: In this experiment, we will realize K-means clustering algorithm (K-means) and understand its working principle in data clustering and its application in image compression. The data sets used in this experiment include: ex3data1.mat -2D datasethzau.jpeg - an image used to test the image compression performance of k-means c ...

brief introduction Simply put: in the distance space, if most of the k nearest neighbors of a sample belong to a category, the sample also belongs to this category. API official website link api class sklearn.neighbors.KNeighborsClassifier(n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_par ...

Pytoch machine learning (x) -- anchor generated by k-means clustering method in YOLO catalogue Pytoch machine learning (x) -- anchor generated by k-means clustering method in YOLO preface 1, K-means clustering   k-means code k-means + + algorithm 2, k-means clustering is used to generate anchor in YOLO Read VOC ...

        Hello, everyone! This article is a follow-up to the previous article. Different from the previous one, this time, the Bayesian classifier is used for number recognition. Bayesian has been taught in probability theory and mathematical statistics. Let's briefly understand it below:         First, t ...

Chapter VI fundamentals of visual processing 6.1 introduction to convolutional neural network          The convolution neural network is composed of one or more convolution layers and the top fully connected layer (corresponding to the classical neural network), as well as the correlation weight and Poo ...

Similar to other data preprocessing of machine learning, natural language processing also needs text preprocessing, such as word segmentation in Chinese and part of speech restoration in English. Common pretreatment methods 1. Text normalization Capital to lowercase output_str = input_str.lower() Digital processing Remove all numbers imp ...

         Chapter 9 optimization methods and regularization          Almost all deep learning is supported by a very important algorithm: random gradient descent (SGD).          So far, we have a deep understanding of the con ...

Introduction to Numpy Numpy (Numerical Python) is an open source Python scientific computing library, which is used to quickly process arrays of arbitrary dimensions. Numpy supports common array and matrix operations. For the same numerical calculation task, using numpy is much simpler than using Python directly. Numpy uses the ndarray obj ...