---
title: Model Selection
description: "Model selection is the process of choosing between different models built on the same data for a machine learning project, e.g., default k-NN model vs logistic regression model vs SVM model vs k-NN model with k=20, etc. Model selection is…"
url: "https://sdscope.com/doc/model-selection-2/"
updated: "2022-06-03"
category: 7. Modeling / 8. Predictive Modeling
---

# Model Selection

Model selection is the process of choosing between different models built on the same data for a machine learning project, e.g., default k-NN model vs logistic regression model vs SVM model vs k-NN model with k=20, etc.

Model selection is generally a trade-off amongst certain qualities, including:
**Simplicity:** humans can easily understand how the model works
**Transparency:** humans can see why the model makes its predictions; this is especially important in regulated industries such as healthcare and banking
**Performance metrics**
**Speed:** to train and test
**Scalability:** ability to be applied to a large dataset

IMPORTANT: Always evaluate models on validation set.

- Join WhatsApp group [here](https://chat.whatsapp.com/G9evrFRKZwwJ0J0OHI6NI7)
- Join Facebook group [here](https://www.facebook.com/groups/artificialintelligenceforeveryone)