Regression — Complete Guide
Regression — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ML.NET Tutorial on Toolliyo Academy.
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ML.NET Tutorial · Lesson 12 of 100
Regression
Foundations → Models → NLP & advanced → MLOps
Foundations · 1 — Context & data · ~6 min · Module 2: Machine Learning Basics
What is this?
Regression predicts continuous numbers — sales, price, demand — not class labels.
Why should you care?
AIPredict forecasting modules need MAE/R², not accuracy %.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
var pipeline = ml.Transforms.CopyColumns("Label", "Revenue")
.Append(ml.Transforms.Concatenate("Features", "Lag1", "Month", "RegionId"))
.Append(ml.Regression.Trainers.Sdca());What happened?
- Label is float.
- Evaluate with Regression.Evaluate.
- Features should relate to the target without leakage.
Practice next
- CopyColumns Label.
- Sdca regressor.
- Print MAE and RSquared.
- Add Lag3 feature.
- Compare FastTree regression.
Remember
Continuous Label. Regression trainers. MAE/R².
AIPredict revenue regressor
Sales forecast trains on lags.
Outcome: MAE beats naive average.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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