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.


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