# logistic regression classifier wikipedia

Logistic Regression is one of the basic and popular algorithm to solve a classification problem. It is named as ‘Logistic Regression’, because it’s underlying technique is quite the same as Linear Regression. The term “Logistic” is taken from the Logit function that is used in this method of classification

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• ### sklearn.linear_model.logisticregression scikit-learn 0

Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the ‘multi_class’ option is set to ‘ovr’, and uses the cross-entropy loss if the ‘multi_class’ option is set to ‘multinomial’

• ### logistic regression for machine learning

Aug 15, 2020 · Logistic regression is another technique borrowed by machine learning from the field of statistics. It is the go-to method for binary classification problems (problems with two class values). In this post you will discover the logistic regression algorithm for …

• ### logistic regression in python real python

Logistic regression is a fundamental classification technique. It belongs to the group of linear classifiers and is somewhat similar to polynomial and linear regression. Logistic regression is fast and relatively uncomplicated, and it’s convenient for you to interpret the results

• ### cis520 machine learning | lectures / logistic

Sep 14, 2017 · Logistic Regression. We saw how a generative classifier, the Naive Bayes model, works. It assumes some functional form for {$\hat{P}(X|Y)$}, {$\hat{P}(Y)$} and estimates parameters of P from training data. It then uses Bayes rule to calculate {$\hat{P}(Y|X=x)$}. In generative models, the computation of {$P(Y|X)$} is always indirect, through Bayes rule

• ### how the logistic regression model works - dataaspirant

Mar 02, 2017 · The logistic regression model is one member of the supervised classification algorithm family. The building block concepts of logistic regression can be helpful in deep learning while building the neural networks. Logistic regression classifier is more like a linear classifier which uses the calculated logits (score) to predict the target class

• ### logistic regression classifier. how it works (part-1) | by

Mar 04, 2019 · Logistic Regression is a ‘Statistical Learning’ technique categorized in ‘Supervised’ Machine Learning (ML) methods dedicated to ‘Classification’ tasks. It has gained a tremendous reputation for last two decades especially in financial sector due …

• ### logistic regression classifier. how it works (part-2) | by

Mar 04, 2019 · Logistic Regression vs. Naîve Bayes: This is actually understanding the differences between ‘Discriminative’ and ‘Generative’ models. Here exists a brief but an elegant post. G. Appendix G.1. Footnotes  Complementary subgroup is called ‘Generative Models’ has members like ‘Naîve Bayes’ and ‘Fisher’s Linear Discriminants’

• ### what makes logistic regression a classification algorithm

Jul 03, 2020 · The Logistic Regression can be explained with Logistic function, also known as Sigmoid function that takes any real input x, and outputs a probability value between 0 and 1 which is defined as, The model fit using the above Logistic function can be seen as below: Logistic Regression on categorical data — By Author

• ### 4.2 logistic regression | interpretable machine learning

A solution for classification is logistic regression. Instead of fitting a straight line or hyperplane, the logistic regression model uses the logistic function to squeeze the output of a linear equation between 0 and 1. The logistic function is defined as: logistic(η) = 1 1 +exp(−η) logistic (η) = 1 1 + e x p (− η)