Isolation Forest (iForest) | Anomaly Detection | Explained with Example

RoboSathi · Beginner ·📐 ML Fundamentals ·5mo ago

Skills: Supervised Learning53%

About this lesson

📘Notes:- https://robosathi.com/docs/machine_learning/unsupervised/anomaly_detection/isolation-forest/ 🎥 NLP Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxcDlHCeNiKbRhLWKVunQaxn 🎥 Deep Learning Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxe749nPGDV2cd6SR6zIZIJl 🎥 Machine Learning Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxeydAqz2lsSMFYinbrJy9mu 🎥 Full Maths Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxen-R6NytSMigAri7piPhFp 🎥 Next Video: Random Sampling Consensus (RANSAC) :- https://youtu.be/H9IfmU1mJzI 🎥 Related Videos: 1) Decision Trees in Machine Learning :- https://youtu.be/yBNQERShy-A 👉 In this video, we explain Isolation Forest (iForest) — a powerful and intuitive algorithm for anomaly detection. 🎯 Learning Objectives ✅ Understand when and why Isolation Forest is used ✅ Understand anomaly detection through a step-by-step example ✅ Learn the Isolation Forest algorithm intuitively ✅ Understand path length, anomaly score, and scoring function 👉 Maths for ML Playlist: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxePOg6k6vAkcg5Y50EAZds9 🕔 Time Stamp 🕘 00:00:00 - 00:00:32 Introduction 00:00:33 - 00:02:42 Use case for Isolation Forest (iForest) 00:02:43 - 00:03:30 Finding Outliers is Easier than a Normal Point 00:03:31 - 00:06:13 Problem & Solution 00:06:14 - 00:07:37 Randomly Partition the Data 00:07:38 - 00:10:01 Understand iForest with Example 00:10:02 - 00:12:47 Algorithm 00:12:48 - 00:14:28 Scoring Function 00:14:29 - 00:18:37 Anomaly Score 00:18:38 - 00:20:30 Drawbacks of iForest 00:20:31 - 00:21:10 What's Next? 🤔 #ai #ml #iforest #anomaly #anomalydetection

Original Description

📘Notes:- https://robosathi.com/docs/machine_learning/unsupervised/anomaly_detection/isolation-forest/ 🎥 NLP Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxcDlHCeNiKbRhLWKVunQaxn 🎥 Deep Learning Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxe749nPGDV2cd6SR6zIZIJl 🎥 Machine Learning Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxeydAqz2lsSMFYinbrJy9mu 🎥 Full Maths Course: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxen-R6NytSMigAri7piPhFp 🎥 Next Video: Random Sampling Consensus (RANSAC) :- https://youtu.be/H9IfmU1mJzI 🎥 Related Videos: 1) Decision Trees in Machine Learning :- https://youtu.be/yBNQERShy-A 👉 In this video, we explain Isolation Forest (iForest) — a powerful and intuitive algorithm for anomaly detection. 🎯 Learning Objectives ✅ Understand when and why Isolation Forest is used ✅ Understand anomaly detection through a step-by-step example ✅ Learn the Isolation Forest algorithm intuitively ✅ Understand path length, anomaly score, and scoring function 👉 Maths for ML Playlist: https://www.youtube.com/playlist?list=PLnpa6KP2ZQxePOg6k6vAkcg5Y50EAZds9 🕔 Time Stamp 🕘 00:00:00 - 00:00:32 Introduction 00:00:33 - 00:02:42 Use case for Isolation Forest (iForest) 00:02:43 - 00:03:30 Finding Outliers is Easier than a Normal Point 00:03:31 - 00:06:13 Problem & Solution 00:06:14 - 00:07:37 Randomly Partition the Data 00:07:38 - 00:10:01 Understand iForest with Example 00:10:02 - 00:12:47 Algorithm 00:12:48 - 00:14:28 Scoring Function 00:14:29 - 00:18:37 Anomaly Score 00:18:38 - 00:20:30 Drawbacks of iForest 00:20:31 - 00:21:10 What's Next? 🤔 #ai #ml #iforest #anomaly #anomalydetection

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Chapters (11)

00:00:32 Introduction

0:33 00:02:42 Use case for Isolation Forest (iForest)

2:43 00:03:30 Finding Outliers is Easier than a Normal Point

3:31 00:06:13 Problem & Solution

6:14 00:07:37 Randomly Partition the Data

7:38 00:10:01 Understand iForest with Example

10:02 00:12:47 Algorithm

12:48 00:14:28 Scoring Function

14:29 00:18:37 Anomaly Score

18:38 00:20:30 Drawbacks of iForest

20:31 00:21:10 What's Next? 🤔

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