Regression analysis - Simple English Wikipedia, the free encyclopedia

Regression analysis is a field of statistics. It is a tool to show the relationship between the inputs and the outputs of a system. Regression analysis is often used for prediction of trends. It is also used for studying whether one thing causes another.

The first type of regression analysis was linear regression. The method of least squares was first published by Legendre in 1805^[1] and in 1809 by Gauss.^[2] Both used the method to predict the movement of planets around the sun. Gauss published an improved method in 1821.

Related pages[change | change source]

References[change | change source]

↑ A.M. Legendre. Nouvelles méthodes pour la détermination des orbites des comètes (1805). “Sur la Méthode des moindres quarrés” is an appendix.
↑ C.F. Gauß. Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientum. (1809)

This short article about mathematics can be made longer. You can help Wikipedia by adding to it.

[Legendre-1] A.M. Legendre. Nouvelles méthodes pour la détermination des orbites des comètes (1805). “Sur la Méthode des moindres quarrés” is an appendix.

[Gauss-2] C.F. Gauß. Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientum. (1809)

[1]

[2]

v t e Machine learning evaluation metrics
Regression	MSE MAE sMAPE MAPE MASE MSPE RMS RMSE/RMSD R² MDA MAD
Classification	F-score P4 Accuracy Precision Recall Kappa MCC AUC ROC Sensitivity and specificity Logarithmic Loss
Clustering	Silhouette Calinski-Harabasz Davies-Bouldin Dunn index Hopkins statistic Jaccard index Rand index Similarity measure SMC SimHash
Ranking	MRR DCG NDCG AP
Computer Vision	PSNR SSIM IoU
NLP	Perplexity BLEU
Deep Learning Related Metrics	Inception score FID
Recommender system	Coverage Intra-list Similarity
Similarity	Cosine similarity Euclidean distance Pearson correlation coefficient
Confusion matrix