My first Classifier Program in Weka
As I explained about the top-down approach, to get the feel of a ML program, I took up my first ML program (specifically a classifier program) in Weka platform.
I followed this article step by step and executed the program successfully. Since this article explains in detail, I’m not going to repeat what is already exist in that article.
However, I will definitely highlight key take-away for me from this exercise.
1. Got a very high level understanding of the process/steps involved in solving a problem using ML.
2. Got to know an objective of a problem statement (classification of Iris Flowers) and how data set matters.
3. Also understood the fact that choosing a ML model which provides better Classification Accuracy is an important factor.
4. I learnt about Confusion Matrix, which provides us True Positive, True Negative, False Positive, and False Negative rates.
This was just a beginning and there are so many things I need to learn in this journey! Though I didn’t get the complete picture now, I am happy that I executed my first ML program.