Logistic Regression

17 problems

• Binary classification with logistic regressionEasy
• Binary output head — probability and decisionEasy
• Huber & Hinge lossesEasy
• k-NN classification (majority vote)Easy
• 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
• Pegasos kernel SVMMedium
• Platt ScalingMedium