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In the previous period, I learned how to summarize the results of univariate Cox regression. In this period, I learned the summary of univariate Logistic regression scores. Because the two functions of coxph * * * * and glm are used, the display of results is different, so the sorting process is slightly different, but the extracted information ...

Article catalog preface1, What is the Dataset class?2, Rewrite steps1. Import and storage2. Data set introduction3. Data set rewriting4. Dataset callsummary preface When reproducing the previous papers, the author wrote the data set processing in the source code, but now most of the code written by pytorch uses Dataset class combined ...

introduce No matter how powerful, machine learning cannot predict everything. For example, in the field related to time series prediction, the performance is not very good. Although a large number of autoregressive models and many other time series algorithms are available, the target distribution cannot be predicted if the target distribut ...

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 ...

Markov models are often used to analyze a large number of random events After a discrete event occurs, another discrete event will occur with a certain probability under the condition of the previous event. For example, we can establish a Markov model for a weather system: In this weather system model, if it is sunny today, there is 70% possib ...

Neural network foundation and multi class classification 3.1 model representation 3.1.1 why do we need neural networks Both linear regression and logistic regression learned in the first two sections have a disadvantage: when there are too many features, the calculation load will be very large. For example, in identifying whether a pictu ...

Five implementation strategies of spatial shift operation in Python This article has authorized the platform of the polar city and is the official account of the polar platform. No second reprint is allowed without permission Original document (may be further updated): https://www.yuque.com/lart/ugkv9f/nnor5p preface Previously, I read ...

Implementation of linear non separable support vector machine    in the article of support vector machine, we have derived the mathematical model of linear non separable support vector machine in detail, and transformed the original problem into a dual problem to be solved. Revisit the dual problem as follows: Final form of dual ...

Implementation of nonlinear support vector machine Suppose that the nonlinear problem we face is the following two classification problem:    it requires us to find a suitable curve that can correctly distinguish red and blue sample points. There is no doubt that linear support vector machine can not solve this kind of problem. We ...

Based on Weka platform, the attribute weighted naive Bayesian algorithm based on differential evolution algorithm is studied Personal interest, hope to help you preface    naive Bayesian algorithm is widely used because of its high classification accuracy and simple model, but it is difficult to realize in practical classif ...