I was in such a rush to finish Project 3 by Sunday night, I didn’t post about the rest of my results, and now before I got a chance to write about it, the professor has already graded it! I got 100% on this one I just turned in, and also just found out I got 100% on Project 2!! This makes me feel so good, especially since I didn’t do so well on the midterm, and confirms that I can do this!
Category: python
ML Project 3 (Post 2)
Tonight I have learned how to use PyBrain’s Feed-Forward Neural Networks for Classification. Yay! I had already created a neural network and used it on the project’s regression data set earlier this week, then used those results to “manually” classify (by picking which class the output was closer to, then counting up how many points… Continue reading ML Project 3 (Post 2)
Machine Learning Project 3
I’m in the midst of working on Project 3 for my Machine Learning class. This one has the following tasks: Train a 3-layer (input, hidden, output) neural network with one hidden layer based on the given training set which has 8 inputs and 7 outputs. Obtain training & testing errors with the number of hidden… Continue reading Machine Learning Project 3
ML Project 2 (Post 2)
I finished the Linear Regression & Classification project for Machine Learning class tonight. The part that took me the longest was definitely the conversion of the C sample code to Python! I can read C OK, but have never written more than the most basic code in C, and want to learn Python as well… Continue reading ML Project 2 (Post 2)
ML Project 1: Summary
In class on Thursday, it turned out that I was 1 of only 2 of the 12 students that had actually finished the project, and the professor gave an extension because he realized that he had forgotten to post a file that would help us understand the data and what we needed to do! I… Continue reading ML Project 1: Summary
ML Project 1 (Post 6)
I will post again on this project later to summarize everything that I learned, and hopefully clean up the code a bit now that I’m not under a time constraint to just get enough done to turn in! Also, now that I’ve submitted my work, any advice on the approach is welcome! The 4 classification… Continue reading ML Project 1 (Post 6)
ML Project 1 (Post 5): Done!
I’m not going to write up the results here and post the code yet because it’s 3am and I still have to write up my project to turn it in, but I wanted to post to say I got the KNN and Gaussian KDE algorithms working tonight! (At least I think they’re working properly.) I’m… Continue reading ML Project 1 (Post 5): Done!
ML Project 1 (Post 4)
Wow, this was a tough one!! I actually had the right idea for this Gaussian Bayes Classifier from the start, but I got totally stuck because my Gaussian values were coming out as 2×2 matrixes instead of probabilities. It turns out my x-mu vectors were being stored as arrays, not matrixes, and in Python, arrays don’t have the same shape. So I don’t know why it didn’t get an error, but the math was coming out all wonky.
I stepped through each piece of that equation, and eventually discovered the “shape” property, which showed me that what I thought was a matrix and a matrix transpose were being seen as the same shape.
ML Project 1 (Post 3)
I present to you… my first classifier! Naive Bayes! It appears to work! haha :)
I know it’s a mess, but I have barely used Python before, and I’m new to Machine Learning, so I’m learning. This is for #2 for my project.
ML Project 1 (Post 2)
So, my Machine Learning project is due in 5 days. We’ve had it since just over a week ago, but also had a homework due in the meantime, so I’m just getting to it. I only have a short time to understand how to do this project, plus I have homework in another class due… Continue reading ML Project 1 (Post 2)