Concerning Classification algorithms, what are the characteristics of Logistic Regression?1 pointThe model is just parameters, fitting can be slow, prediction is fast, and the decision boundary is simple and less flexibleThe training data is the model, fitting is fast, prediction is fast, and the decision boundary is flexibleThe model is just parameters, fitting is fast, prediction is fast, and the decision boundary is flexibleThe training data is the model, fitting is fast, predicting class for new records can be slow, and the decision boundary is flexible

Which one is a classification algorithm?(1 Point)Logistic regressionLinear regressionPolynomial regressionNone

What is a logistic regression algorithm?Question 8Answera.A model used for classification tasks by predicting the probability of an event occurringb.A clustering algorithm used in unsupervised learningc.A linear model used to make predictions in supervised learningd.A tree-like model used to make predictions in supervised learning

What type of problems is logistic regression typically used for?Answer choicesSelect only one optionREVISITRegression problemsBinary classification problemsMulti-class classification problemsClustering problems

Question 1These are all characteristics of decision trees, EXCEPT:1 pointThey have well rounded decision boundariesThey split nodes into leavesThey can be used for either classification or regressionThey segment data based on features to predict results

Logistic regression can only be used when (Select one) A. you have a numerical label and numerical attributes. B. you have a binominal label and numerical attributes. C. you have a numerical label and polynominal attributes. D. the data is from a logistics use case.