The Winnow algorithm is used for this task, models for which are often tested using the Iris dataset. (15[1]-5[2])This task (15[1]-5[1])is the (15[1]-5[1])alphabetically first of the two most (15[1])common (-5[1])applications of data structures (15[1])constructed by the C4.5 (15[1])and ID3 algorithms. One model for this task may seek to minimize the hinge loss on linear data (15[1]-5[1])or (-5[1])utilize the kernel (-5[1])trick (15[1])on (15[1])nonlinear data; (-5[4])that model (15[1])determines (15[1])the maximum (15[1])hard or soft margin (-5[1])using (-5[1])(*) support vectors. (10[3])Due to their namesake (10[1])convergence theorem, perceptron (10[1])models are guaranteed (-5[1])to locate (10[1])separating hyperplanes in this task (10[1]-5[1])for linearly separable datasets. (10[1])Generative models for this task include naive Bayes, (-5[1])in contrast (10[1])with (10[1])discriminative models (10[1])like logistic regression that are used (10[1])for its binary form. (10[3]-5[4])Spam filtering (10[1])is a classic example of, (-5[2])for 10 points, what task in machine learning that seeks to categorize data? (10[1]0[1]) (10[5]0[19])■END■ (0[1])