Linear Regression

26 problems

• Regression vs classification outputEasy
• Scaling laws — estimate the power-law exponentMedium
• Elastic-Net regression (gradient descent)Medium
• Gaussian process regression (RBF)Hard
• Huber & Hinge lossesEasy
• Linear regression — gradient descentEasy
• Linear regression — normal equationMedium
• Linear regression — sum of squared residuals (SSR)Easy
• Linear regression — one gradient descent stepEasy
• Linear regression — predict with a lineEasy
• Linear regression — residualsEasy
• Logistic regression — gradient descentMedium
• Logistic regression — the BCE gradient (error × feature)Easy
• Logistic regression — binary cross-entropy lossEasy
• Logistic regression — classify at a thresholdEasy
• Logistic regression — likelihood of the whole datasetEasy
• Logistic regression — which side of the decision boundaryEasy
• Logistic regression — probability of the true labelEasy
• Logistic regression — probability from a scoreEasy
• Logistic regression — the sigmoid reflection identityEasy
• Logistic regression — when a linear score isn't a probabilityEasy
• Logistic regression — two-class probabilitiesEasy
• Pinball (Quantile) Regression LossMedium
• Ridge regression lossEasy
• Softmax (multinomial) regressionMedium
• Sorted polynomial featuresMedium