Write the necessary python code (spyder python) to read the dataset file in the photo and perform classification using 5 supervised learning models Bagging , boosting , stacking ,decision tree, K-Neighbors). Note that for each model draw the confusion matrix and compute the Accuracy, Recall, Precision and F1-Measure

\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|c|c|} \hline Person to & Gender & Age & Occupstion & Sleep Duration & Quality of Sieep & Physical Activity Level & Stress Level & BMI Category & Blood Pressure & Heart Rate & Daily Steps & Sleep Disorder \\ \hline 1 & Male & 27 & Software Engineer & 6.1 & 6 & 42 & 6 & Overweight & 126/83 & n7 & 4200 & None \\ \hline 2 & Male & 28 & Dector & 6.2 & 6 & 60 & B & Normal & 125/80 & 75 & 10000 & None \\ \hline 3 & Male & 2in & Dectar & 6.2 & 6 & 60 & B & Normal & 125/80 & 75 & 10000 & None \\ \hline 4 & Maie & 20 & Sales Representative & 5.9 & 4 & 30 & n & obese & 140/90 & is & 3000 & Sleep Apnea \\ \hline \end{tabular}