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Questions and Answers
What is the main challenge in finding the optimal coefficients for a logistic regression model?
What is the main challenge in finding the optimal coefficients for a logistic regression model?
- The choice of solver
- The infinite number of possible combinations (correct)
- The complexity of the model
- The lack of data
What is the purpose of gradient descent in logistic regression?
What is the purpose of gradient descent in logistic regression?
- To visualize the data
- To find the optimal coefficients (correct)
- To predict the class probabilities
- To evaluate the model performance
What is the formula for the partial derivative of the loss function with respect to a parameter θj?
What is the formula for the partial derivative of the loss function with respect to a parameter θj?
- ∂/∂θj J(θ) = 1/m * Σ [xj - y(i)]
- ∂/∂θj J(θ) = 1/m * Σ [σ(θT * x) - y(i)] (correct)
- ∂/∂θj J(θ) = 1/m * Σ [xj * σ(θT * x)]
- ∂/∂θj J(θ) = 1/m * Σ [y(i) - σ(θT * x)]
What is the purpose of the batch gradient descent algorithm?
What is the purpose of the batch gradient descent algorithm?
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What is the main difference between stochastic gradient descent and mini-batch gradient descent?
What is the main difference between stochastic gradient descent and mini-batch gradient descent?
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What is the purpose of the logistic regression model in the iris example?
What is the purpose of the logistic regression model in the iris example?
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What is the output of the logistic regression model in the iris example?
What is the output of the logistic regression model in the iris example?
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What is the purpose of the plot in the iris example?
What is the purpose of the plot in the iris example?
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How is the class predicted in the logistic regression model?
How is the class predicted in the logistic regression model?
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What is the advantage of using logistic regression over linear regression?
What is the advantage of using logistic regression over linear regression?
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