What is the difference between classifiers and models?
Hi,
I'm trying to understand what a model and what a classifier is in machine learning. It is my current understanding that classifiers are things like linear regression, neural network and decision trees.
Thank you
Hey Nico,
Thank you for your question!
A classifier/regressor/clustering algorithm refers to the type of machine learning algorithm you have chosen to work with - Linear regression, Logistic regression, K-Means clustering, etc.
This becomes a model once you have set the hyperparameters of your classifier during the training/validation process.
For example, let's assume you have a clustering problem and have decided to use K-Means clustering to solve it. Once you have chosen the value of K that works best for your problem (and maybe the values of other parameters that you can fine-tune), then you have created a model. You then test your model on the test dataset and evaluate its performance.
Hope this helps!
Kind regards,
365 Hristina
