Last time, I have introduced the evaluation metrics used for the LTN classification task. Today, I will show some first results of the k nearest neighbor (kNN) classifier which will serve as a baseline for our LTN results.
Category: Conceptual spaces
Applying Logic Tensor Networks (Part 2)
In my last LTN blog post, I introduced the overall setting of my experiment. Before I can report on first results, I want and need to describe how we can evaluate the performance of the classifiers in this multi-label classification setting. This is what I’m going to do today.
How does multidimensional scaling work?
I have already talked about multidimensional scaling (MDS) some time ago. Back then, I only gave a rough idea about what MDS does, but I didn’t really talk much about how MDS arrives at a solution. Today, I want to follow up on this and give you some intuition about what happens behind the scenes.
Applying Logic Tensor Networks (Part 1)
In previous blog posts I have already talked about Logic Tensor Networks in general, their relation to Conceptual Spaces, and several additional membership functions that are in line with the Conceptual Spaces framework. As I already mentioned before, I want to apply them in a “proof of concept” scenario. Today I’m going to sketch this scenario in more detail.
CARLA Summer School and Workshop
It has been quite some time since my last blog post (more than two months actually!) and the question is: What has happened?
Well, CARLA has happened – an interdisciplinary and international summer school with a co-located workshop.