Programming VIP

Objective: to predict whether a college student can be admitted to the university according to the score. Methods: call the advanced optimization algorithm or write the gradient descent function (choose the learning rate and iteration times by yourself) Data: ex2data1 txt 1, Read in data. 1.1 INTRODUCTION Kit import numpy as np import pa ...

Series articles Chapter VIII Teach you hand in hand: Stock Forecasting System Based on LSTMChapter VII Teach you by hand: fruit classification and recognition system based on depth residual network (ResNet)Chapter VI Hand in hand teach you: face recognition video coding 1, Project introduction This paper mainly introduces how to us ...

We will build a logistic regression model to predict whether a student is admitted to the University. Suppose you are an administrator of a university department. You want to decide the admission opportunity of each applicant according to the results of two exams. You have the historical data of previous applicants, and you can use it as th ...

preface Softmax regression, also known as multiple or multi class Logistic regression, is the generalization of Logistic regression in multi classification problems. 1, Training set and test set Use the data set fashion MNIST obtained in the previous section. 2, Steps 1. Import and storage import torch import torchvision import nu ...

Catalogue   I Manual push to achieve logistic regression gradient descent II Classification of iris data set by logistic regression      1. Introduction to iris data set      2. What is a linear classifier      3. Main steps of designing linear classifier      4. Rough defin ...

Original link: http://tecdat.cn/?p=24973  Original source: Tuo end data tribal official account brief introduction The World Health Organization estimates that 12 million people worldwide die of heart disease every year. In the United States and other developed countries, half of the deaths are due to cardiovascular disease. The early ...

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 ...

Data links and codes: https://pan.baidu.com/s/19Rj_kP2iJ0szS6l2IWg6FQ  Extraction code: ezbd 1. Data analysis Dataset divorce Xlsx, let's take a look at the data description first. In short, each dimension corresponds to a questionnaire question. As shown in the figure Libraries to be imported: import pandas as pd import numpy as np ...

1, Classification prediction based on logistic regression 1 Introduction and application of logistic regression 1.1 introduction to logistic regression Although Logistic regression (LR) has the word "regression", it is actually a classification model and is widely used in various fields. Although deep learning is more popular t ...