binary classification

Model Perspective

Aug 23, 2023 · Artificial Intelligence

Master Logistic Regression: Binary, Multiclass, and Ordered Extensions with Python

This article explains logistic regression and its extensions—binary, multiclass (softmax), and ordered logistic regression—covering mathematical foundations, optimization objectives, real‑world applications, and Python implementations using scikit‑learn with code examples and visual illustrations.

binary classificationlogistic regressionmulticlass classification

0 likes · 15 min read

Master Logistic Regression: Binary, Multiclass, and Ordered Extensions with Python

Model Perspective

Dec 4, 2022 · Fundamentals

How Logistic Regression Predicts Titanic Survival: A Step-by-Step R Guide

This article explains logistic regression for binary outcomes, demonstrates its implementation in R with the TitanicSurvival dataset, and interprets the model coefficients showing how gender, age, and passenger class significantly affect survival probability.

RTitanic datasetbinary classification

0 likes · 5 min read

How Logistic Regression Predicts Titanic Survival: A Step-by-Step R Guide

Alimama Tech

May 13, 2021 · Artificial Intelligence

Fundamentals and Misconceptions of CTR (Click-Through Rate) Modeling

CTR modeling predicts click probabilities despite inherent microscopic randomness, treating each impression as an i.i.d. Bernoulli event and framing the task as binary classification; because data are noisy and imbalanced, evaluation relies on AUC rather than accuracy, with theoretical upper bounds set by feature quality, and calibration is needed to align predicted values with observed frequencies.

AUCbinary classificationclick-through rate

0 likes · 20 min read

Fundamentals and Misconceptions of CTR (Click-Through Rate) Modeling

JD Tech Talk

Mar 29, 2019 · Artificial Intelligence

Understanding Confusion Matrix, ROC Curve, and Evaluation Metrics for Binary Classification Models

After building a binary classification model, this article explains essential evaluation tools such as the confusion matrix, derived metrics like accuracy, precision, recall, F1 score, and the ROC curve, illustrating their definitions, visualizations, and practical considerations for different business scenarios.

F1 scorePrecisionROC curve

0 likes · 6 min read

Understanding Confusion Matrix, ROC Curve, and Evaluation Metrics for Binary Classification Models

UC Tech Team

Nov 5, 2018 · Artificial Intelligence

News Page Identification Using Machine Learning: Feature Engineering, Model Selection, and Evaluation

To accurately distinguish news pages from other web page types, this study formulates the task as a binary classification problem, extracts 19 engineered features from HTML, evaluates logistic regression and SVM models with cross‑validation, and achieves over 90% precision, recall, and F1‑score using LR with Newton method.

SVMbinary classificationfeature engineering

0 likes · 13 min read

News Page Identification Using Machine Learning: Feature Engineering, Model Selection, and Evaluation

Qunar Tech Salon

Dec 5, 2017 · Information Security

Machine Learning Practices for Web Attack Detection at Ctrip

This article describes Ctrip’s evolution from rule‑based web attack detection to a Spark‑powered machine‑learning system, detailing the Nile architecture, data collection, feature engineering with TF‑IDF, model training, evaluation metrics, online deployment, and future enhancements for information security.

Sparkattack detectionbinary classification

0 likes · 17 min read

Machine Learning Practices for Web Attack Detection at Ctrip

Art of Distributed System Architecture Design

Oct 6, 2015 · Artificial Intelligence

Feature Engineering and PCA for Binary Classification in R

This article explains how feature engineering and principal component analysis (PCA) can be applied to a two‑feature binary classification problem in R, illustrating data exploration, model evaluation with ROC AUC, and the impact of dimensionality reduction on predictive performance.

PCARbinary classification

0 likes · 9 min read

Feature Engineering and PCA for Binary Classification in R