output confusion matrix[[ ]classification reportprecision recall -score support iris-setosa iris-versicolor iris-virginica micro avg macro avg weighted avg accuracy pros and cons of random forest pros the following are the advantages of random forest algorithmit overcomes the problem of overfitting by averaging or combining the results of different decision trees random forests work well for large range of data items than single decision tree does random forest has less variance then single decision tree random forests are very flexible and possess very high accuracy scaling of data does not require in random forest algorithm it maintains good accuracy even after providing data without scaling random forest algorithms maintains good accuracy even large proportion of the data is missing cons the following are the disadvantages of random forest algorithm