Week 4
The plan for this week was to develop a decision tree for regression.
Day 1:
- I spent the whole day studying how decision tree is implemented in ECL. It was one complex code and since I am new to ECL it was a lot to take.
- I realized that the core logic of the splitting criteria is a very small part and most of the code is data transformation
- Once that sunk in, I know what to do.
Day 2:
- The choice to choose the splitting criteria was the next challenge.
- The simplest decision tree to implement I think is the standard deviation based ID3 algorithm and I spent the day reading about it.
- I also implemented the stub methods for the decision tree.
Day 3:
- The day was spent implementing the splitting criteria and completed it.
Day 4:
- The first half of the day was spent attending a talk by Jamie Buckley, the Chief Product Officer.
- He gave a nice talk on his journey in the tech industry and all the cutting edge technology at Lexis Nexis.
- I was really impressed by the work in Machine Learning especially the Socrates project.
- I spent the rest the day, completing the learning and prediction functions.
Day 5:
- There was a small bug in the predict function and I spent some time fixing it.
- I implemented a small test for verifying the implementation of Decision Tree and compared it against Linear Regression.
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