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      Question

      'Logistic regression'

      is:
      A A regression technique for predicting continuous numerical values like house prices Correct Answer Incorrect Answer
      B A classification algorithm that models the probability of a binary outcome (0 or 1) using the sigmoid function Correct Answer Incorrect Answer
      C A clustering algorithm for grouping similar customers together Correct Answer Incorrect Answer
      D A time-series algorithm for forecasting future sales and revenue Correct Answer Incorrect Answer
      E A dimensionality reduction technique for compressing feature space Correct Answer Incorrect Answer

      Solution

      Logistic Regression uses the sigmoid function to map any real-valued input to a probability between 0 and 1 using P(Y=1) = 1/(1 + e^(-z)). A threshold (typically 0.5) converts probabilities to class predictions. Output is interpretable as log-odds (coefficients) show feature importance and direction. It assumes linear relationship between features and log-odds. Logistic regression is used in banking for Binary credit decisions (approve/reject), fraud detection (fraud/not fraud) and churn prediction (leave/stay). It can be extended to multi-class via softmax (multinomial logistic regression). Despite its name, it is a classification, not a regression, algorithm.

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