Tag:matrix
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Time:2021-1-25
In mathematics, a matrix is a rectangular array of numbers, symbols or expressions arranged in rows and columns. Any matrix can be multiplied by the scalar of the related fields. The main application of matrix is to represent the linear transformation, that is, the generalization of linear functions such as f (x) = 4x. For […]
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Time:2021-1-24
From machine learning alchemy Basic concepts First of all, there are several concepts to memorize: accuracy, recall, TP, FP, TN, FN TP:true positive。 The prediction is the correct positive sample FP:false positive。 The prediction is the wrong positive sample TN:true negative。 The prediction is a correct negative sample FP:false positive。 The prediction is the wrong […]
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Time:2021-1-24
In IOS, we can monitor touch events through uitouch, but it is very troublesome to monitor gesture events such as kneading, rotating and long pressing. Provided in IOSUIGestureRecognizerSubclasses of help us achieve simple kneading, rotation and other special gesture monitoring. And a view can add a number of different gesture listeners. Enable user interaction enabled […]
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Time:2021-1-23
definition Transitive closureThat is to say, in mathematics, the transitive closure of binary relation R on set X is the smallest transitive relation on X containing R. Related issues Calculate the transitive relation in a matrix (e.g. the connected relation between two points on a graph) Warshall algorithm is usually used for calculation The calculation […]
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Time:2021-1-20
1、 Environmental preparation Anaconda Download https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/ All operations are in jupyter notebook 2、 Numpy learning 1. Recognize numpy’s array 2. Master numpy array 3. Learn the matrix of numyp 3、 Pandas learning 1. Panda reading and writing Pandas provides a variety of IO operations 1. MySQL reading and writing 2. Panda common read 2. Panda […]
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Time:2021-1-18
Here’s a square matrixmatPlease return the sum of the diagonal elements of the matrix. Please return the sum of the elements on the main diagonal of the matrix and the elements on the sub diagonal and not on the main diagonal. (if the order is odd, the elements of the diagonal intersection will only be […]
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Time:2021-1-18
catalog 1、 Linear regression 2、 Least square method 3、 Least square method (vector representation) 4、 Python implementation 1、 Linear regression given the sample x = (x0, x1, X2,…, xn) described by N attributes,linear modelTry to learn a suitable linear combination of sample attributes to perform the prediction taskf(x) = w1x1 + w2x2 + … […]
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Time:2021-1-17
The upper triangular matrix refers to the matrix whose elements below the main diagonal are all 0; the main diagonal is the line from the upper left corner to the lower right corner of the matrix. This problem requires the preparation of procedures to determine whether a given square matrix is a triangular matrix. Input […]
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Time:2021-1-17
One dimensional array Crud of one dimensional array Crud about arrays is actually very simple. //The. H file of the sequence table #include<iostream> using namespace std; const int MAXSIZE = 20; class SqList{ private: int *data; int length; public: Sqlist(); // constructor ~Sqlist(); // destructor Void creatlist (int a [] int n); // create a […]
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Time:2021-1-12
For more articles, please pay attention to the official account of “BLOG of the sea”. problem Given a matrix A of nxm, find a nonempty submatrix in a to make the sum of elements in the submatrix maximum.The submatrix of a refers to a block in which the row and column are continuous.Input formatThe first […]
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Time:2021-1-9
In this paper, a class specific control gate CSG is proposed to guide the network to learn class specific convolution kernel, and a regularization method is added to sparse the CSG matrix to further ensure class specific. From the experimental results, the sparsity of CSG can guide the strong correlation between convolution kernel and class, […]
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Time:2021-1-5
The most popular dimension reduction algorithm: principal component analysis (PCA) Before applying PCA, we should normalize the mean value and normalize the features, so that the values can be compared PCA target When we reduce the data set from two dimensions to one dimension, we need to find a vector to make the distance between […]