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[P] Ideas for implementing an original supervised machine learning technique?

I’m taking a machine learning class and I have a project, whose task is to implement an original supervised learning algorithm. It doesn’t have to be something new from scratch and it doesn’t need to be overcomplicated, because it’s a one week project. It can be a combination of two learning algorithms that can accurately classify a labeled data set, such as using genetic algorithms with artificial neural networks. It can also use part of an existing algorithm, as long as I add something substantial to it. The problem is I can’t think of a simple idea that is not already proposed in a published research paper.

To put things into perspective, the learning algorithms I’m familiar with are:

  • Decision Trees
  • KNN
  • ANN
  • SVM
  • Linear and Logistic Regression
  • Genetic Algorithm
  • Clustering

submitted by /u/PatientLookout
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.