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Data Science Q&A — (14) Sampling techniques for imbalanced data
Data Science Q&A — (14) Sampling techniques for imbalanced data
Q1. What is class imbalance in supervised learning?
Chris Kuo/Dr. Dataman
Aug 24
Data science Q&A — (13) Regularization
Data science Q&A — (13) Regularization
Q1. What is overfitting in machine learning, and why is it a problem?
Chris Kuo/Dr. Dataman
Aug 24
Data science Q&A — (12) Supervised learning primer
Data science Q&A — (12) Supervised learning primer
Q1. What is supervised learning, and can you name some common algorithms?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (11) Autoencoders
Data Science Q&A — (11) Autoencoders
Q1. What inspired the development of neural networks in artificial intelligence?
Chris Kuo/Dr. Dataman
Aug 24
Data science Q&A — (15) Representation Learning for Outlier Detection
Data science Q&A — (15) Representation Learning for Outlier Detection
Q1: What is the primary goal of feature engineering in anomaly detection in response to evolving anomalous patterns?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (10) CBLOF
Data Science Q&A — (10) CBLOF
Q1. What is the Cluster-Based Local Outlier Factor (CBLOF) and how does it work?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (9) LOF
Data Science Q&A — (9) LOF
Q1. What is the Local Outlier Factor (LOF) algorithm?
Chris Kuo/Dr. Dataman
Aug 24
Data science Q&A — (8) KNN
Data science Q&A — (8) KNN
Q1. What is the k-nearest Neighbors (KNN) algorithm?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (7) GMM
Data Science Q&A — (7) GMM
Q1 How does GMM differ from K-means in terms of cluster assignment
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (6) One-class SVM
Data Science Q&A — (6) One-class SVM
Q1. What is the primary use case for the One-Class Support Vector Machine (OC-SVM)?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (5) PCA
Data Science Q&A — (5) PCA
Q1. What is Principal Component Analysis (PCA) and why is it used?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (4) Isolation Forest
Data Science Q&A — (4) Isolation Forest
Q1. What is the fundamental intuition behind the Isolation Forest algorithm?
Chris Kuo/Dr. Dataman
Aug 24
Data science Q&A — (3) ECOD
Data science Q&A — (3) ECOD
Q1. What are parametric and non-parametric distributions? Provide an example of each.
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (2) HBOS
Data Science Q&A — (2) HBOS
Q1. What is the Histogram-Based Outlier Score (HBOS)?
Chris Kuo/Dr. Dataman
Aug 24
Data Science Q&A — (1) Anomaly Detection
Data Science Q&A — (1) Anomaly Detection
Q1. What is an anomaly in data analysis?
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (X) Instructor’s manual
Handbook of Anomaly Detection — (X) Instructor’s manual
First, we would like to express our appreciation for you to choose this book as your course textbook. We trust this book can assist you…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (14) Sampling Techniques for Extremely Imbalanced Data
Handbook of Anomaly Detection — (14) Sampling Techniques for Extremely Imbalanced Data
In supervised learning, one of the most challenging issues practitioners encounter is the problem of extreme class imbalance. Class…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (13) Regularization
Handbook of Anomaly Detection — (13) Regularization
In the previous chapter, we have covered several key machine learning models including Random Forests, Gradient Boosting Machine (GBM)…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (12) Supervised Learning Primer
Handbook of Anomaly Detection — (12) Supervised Learning Primer
Supervised Learning is a type of machine learning where the algorithm is trained on labeled data. Linear regressions and decision trees…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (11) Autoencoders
Handbook of Anomaly Detection — (11) Autoencoders
Neural networks, also known as Deep Learning, have revolutionized the field of artificial intelligence and machine learning. They have…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (15) Representation Learning for Outlier Detection
Handbook of Anomaly Detection — (15) Representation Learning for Outlier Detection
In Chapter 1, we’ve mentioned the importance of feature engineering to discover new patterns, and the use of unsupervised learning…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (10) Cluster-Based Local Outlier Factor (CBLOF)
Handbook of Anomaly Detection — (10) Cluster-Based Local Outlier Factor (CBLOF)
Following our exploration of the Local Outlier Factor (LOF) in the previous Chapter, we now turn our attention to the Cluster-Based Local…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (9) Local Outlier Factor (LOF)
Handbook of Anomaly Detection — (9) Local Outlier Factor (LOF)
One day I was sitting on a rock on a beach and enjoying the sunset. There was a group of seagulls perched on a nearby rock. There was a…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (8) KNN
Handbook of Anomaly Detection — (8) KNN
The k-Nearest Neighbors algorithm, commonly known as KNN, is a simple and widely used algorithm in classification models, regressions, and…
Chris Kuo/Dr. Dataman
Aug 24
Handbook of Anomaly Detection — (7) GMM
Handbook of Anomaly Detection — (7) GMM
One of the most enchanting aspects of a camping trip for me is stargazing on a calm evening. As I gaze up at the night sky, I’m filled…
Chris Kuo/Dr. Dataman
Aug 24
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