Programming VIP

1, Introduction to LDA theme model LDA topic model is mainly used to infer the topic distribution of documents. The topic of each document in the document set can be given in the form of probability distribution, and topic clustering or text classification can be carried out according to the topic. LDA topic model does not care about the orde ...

Exploration of K-means clustering algorithm import numpy as np import matplotlib.pyplot as plt import sklearn.datasets as ds import matplotlib.colors from sklearn.cluster import KMeans,MiniBatchKMeans def expand(a,b): d=(b-a)*0.1 return a-d,b+d if __name__ == '__main__': N=400 #Create 400 samples centers=4 ...

preface Cell picture data are as follows Cell recognition To classify the cells in the picture, we must first identify the cells in the picture First read the picture, then convert it into a gray image, then Gaussian blur the picture, then convert the picture into a binary image by using an adaptive threshold, and then define an elliptical che ...

Catalog 1. Preface 2. References and Basis 3. Why Linear Regression 4. Problem Analysis 1. Modeling 2. Read in data and get output 3. Loss function 4. Optimization algorithm 6. Model training, prediction labels 1. Preface This article is written in the beginning of the author's in-depth learning, but the understanding is still shall ...

1 Theory AlexNet is an 8-layer deep convolution network, which is mainly applied to images. Innovation of the article: In view of too little data, an amplification method is proposed, such as image clipping / flipping, etcFor the activation function, ReLU is used instead of Sigmoid to overcome the difficulty of training Sigmoid function when ...

catalogue 1, Background 2, Principle 1. Introduction to discrete Laplace operator 2. Laplace convolution 3. Introduction to solution of Possion equation III. verification IV. algorithm implementation in Python a. DCT solution 1. Define the function calMSE calculation error Mean Square Error 2. Import the original drawing and note the ...

Because I didn't choose Linux for my undergraduate course, and I haven't used the Linux system since I was preparing for the competition and maintaining the research. This research 0 now records some environments for in-depth learning using the Linux system for the first time this week~ I First, download the Xshell to operate the terminal. Th ...

catalogue 1, Basic theory of multiple linear regression2, Case analysis3, Data preprocessing 1. Error data cleaning2. Non numerical data conversion 4, Regression using Excel 1. Regression realization2. Regression analysis 5, Regression using code 1. Data preprocessing2. Use Statsmodels to establish multiple linear regression model3. U ...

catalogue reference material 1. Import package 2. Import data 3. View the first 5 rows of data 4. Transformation of categorical variables into dummy variables (gender) Knowledge point - dummy variable 5. Merge data frame 6. Delete unnecessary columns 7. Count the missing value of each line 8. Visual missing value 9. View and visualiz ...

Part III modeling and model evaluation In the first two parts, we have processed the data of the Titanic. Interested partners can take a look at the first two articles. This article mainly introduces the third part of prediction analysis, that is, modeling and model evaluation. After data processing, let's see which model has the highest predi ...