Last answered:

21 Feb 2022

Posted on:

20 Feb 2022


What is the difference between classifiers and models?


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

1 answers ( 0 marked as helpful)
Posted on:

21 Feb 2022


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

Submit an answer