Now, you ought to implement the AdaBoost.M1 and AdaBoost.M2 algorithms. These algorithms are two versions of the AdaBoost algorithm for handling the Problems with more than two classes. You must first read the paper “Experiments with a New Boosting Algorithm”. Use decision stump and C4.5 classifiers of Weka as the base classifiers for AdaBoost.M1 and use decision stump as the base classifier for AdaBoost.M2.

adaboost\adaboostM2.m
........\adaboostM2T.m
........\autoAdaboostM1.m
........\autoadaboostM1T.m
........\autoadaboostM2.m
........\autoadaboostM2New.m
........\autoadaboostM2T.m
........\autos.txt
........\autos.xlsx
........\autosArff.txt
........\autosArfftest.txt
........\autosH.txt
........\autossampleArff.txt
........\editMissigValues.m
........\giveAccuracy.m
........\glass.txt
........\glassAdaboostM1.m
........\glassAdaboostM1T.m
........\glassadaboostM2.m
........\glassadaboostM2T.m
........\glassArff.txt
........\glassArfftest.txt
........\glassH.txt
........\glasssampleArff.txt
........\mainHw2.m
........\mammo.xlsx
........\mammoAdaboostM1.m
........\mammoAdaboostM1T.m
........\mammoAdaboostM2T.m
........\mammoArff.txt
........\mammoArfftest.txt
........\mammographic.txt
........\mammoH.txt
........\mammosampleArff.txt
........\pima.xlsx
........\pimaAdaboostM1.m
........\pimaAdaboostM1T.m
........\pimaAdaboostM2.m
........\pimaAdaboostM2T.m
........\pimaArff.txt
........\pimaArfftest.txt
........\pimaH.txt
........\pimasampleArff.txt
........\q_statistic.m
........\readFile.m
........\returnLabel.m
........\sat.txt
........\satAdaboostM1.m
........\satAdaboostM1T.m
........\satadaboostM2T.m
........\satArff.txt
........\satArfftest.txt
........\satH.txt
........\satsampleArff.txt
........\satTest.txt
........\shuffling.m
........\writeCell.m
........\writeFile.m
........\writeText.m
adaboost

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