مقایسهٔ روشها
روشهای انتخابی خود را کنار هم مرور کنید؛ ردیفهای متفاوت برجسته شدهاند.
| رگرسیون لجستیک (یادگیری ماشین)× | درخت تصمیم× | |
|---|---|---|
| حوزه | یادگیری ماشین | یادگیری ماشین |
| خانواده | Machine learning | Machine learning |
| سال پیدایش≠ | 1958 | 1984 |
| پدیدآور≠ | Cox, D. R. | Breiman, Friedman, Olshen & Stone |
| نوع≠ | Probabilistic linear classifier | Recursive partitioning (if-then rules) |
| منبع بنیادین≠ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ | Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗ |
| نامهای دیگر≠ | logit model, logit regression, binomial logistic regression, maximum entropy classifier | Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree |
| مرتبط | 5 | 5 |
| خلاصه≠ | Logistic regression is a foundational probabilistic classifier that models the log-odds of a binary (or multinomial) outcome as a linear function of the predictors. Introduced by D. R. Cox in 1958, it remains one of the most widely used and interpretable classification methods in both statistics and machine learning, valued for its calibrated probability outputs and clear coefficient interpretation. | A Decision Tree is an interpretable classification and regression method, formalised by Breiman, Friedman, Olshen and Stone in their 1984 CART framework, that partitions the data with hierarchical if-then rules. Each split sends observations down one branch or another until a prediction is read off the leaf. |
| ScholarGateمجموعهداده ↗ |
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