Yes, Logistic Regression is one of the machine learning algorithms which is usually used for binary classification problems. It is a generalized linear model that can be used to estimate the probability that the dependent variable is binary. The output of logistic regression is a probability value between 0 and 1 that can be used to predict which class a new observation belongs to.
Is logistic regression a machine learning algorithm?
The basic principle of logistic regression is to convert the value of the linear combination into a probability value by linearly combining the feature vectors and then inputting this combination into a sigmoid function. The output value of the sigmoid function is between 0 and 1, representing the probability that the dependent variable is 1. If the output value is greater than or equal to 0.5, the predicted result is 1, otherwise it is 0.
Logistic regression is a simple yet effective algorithm that is often used in classification problems such as spam identification, fraud detection, medical diagnosis, etc. In addition, it can also be used for multi-class classification problems, such as softmax regression.
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