We took an iris dataset and trained with different classifiers to find out their accuracy and some parameters.
Here is a dataset with name Iris(1).csv where all the data is present in there. We use 80% of data to train and 20% of data for testing purpose.
We have used different machine learning algorithms to find their parameters like accuracy,precision,f1-score,recall...etc and also plotted different to have a good conclusion.
With the help of pandas we retrieve the data from the Iris(1).csv in the terminal. And also with the help of confusion matrix it is really easy to understand and to find out TT,TF,FT,FF and this confusion matrix can be imported from confusion matrix package.
Finally, with the help of classification_report package we come to a conclusion of all the parameters.