Machine Learning Combat Learning notes 9--logistic regression

1.logistic Regression Overview Introduction to Logistic regression of 1.1

Logistic regression is a generalized linear regression analysis model, which is a multivariable analysis method to study the relationship between two classification observation results y and some influential factors (x_1,x_2,..., x_n). It is usually studied whether a certain outcome occurs in some conditions, such as whether the patient is suffering from a disease based on symptoms in medicine. principle of 1.2 logistic regression

The main idea of the logistic regression classification is: To establish the regression formula of the classification boundary line according to the existing data. advantages and disadvantages of 1.3 logistic regression

(1) Advantages: The calculation cost is not high, easy to understand and realize.
(2) Disadvantage: Easy to fit, the classification of intensive reading may not be high.
(3) Application: Often used in automatic diagnosis of diseases, economic prediction and so on. 2. Using logistic regression to classify