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Machine Learning: Unsupervised Learning - Clustering

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Machine Learning: Unsupervised Learning - Clustering

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Questions and Answers

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?

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?

∂/∂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?

To update the model parameters using the entire training dataset Signup and view all the answers

What is the main difference between stochastic gradient descent and mini-batch gradient descent?

The number of instances used to update the model parameters Signup and view all the answers

What is the purpose of the logistic regression model in the iris example?

To detect the iris-virginica type based on the petal width feature Signup and view all the answers

What is the output of the logistic regression model in the iris example?

A probability distribution Signup and view all the answers

What is the purpose of the plot in the iris example?

To visualize the decision boundary Signup and view all the answers

How is the class predicted in the logistic regression model?

By selecting the class with the highest probability Signup and view all the answers

What is the advantage of using logistic regression over linear regression?

It can handle binary classification problems Signup and view all the answers