logistic regression

Python Programming Learning Circle

Apr 10, 2024 · Artificial Intelligence

Top 10 Machine Learning Algorithms Explained

This article introduces the No‑Free‑Lunch principle in machine learning and provides concise explanations of ten fundamental algorithms—including linear and logistic regression, LDA, decision trees, Naïve Bayes, K‑Nearest Neighbors, LVQ, SVM, bagging with random forests, and boosting with AdaBoost—guiding beginners on how to choose the right model.

AIAlgorithmsSVM

0 likes · 14 min read

Top 10 Machine Learning Algorithms Explained

Rare Earth Juejin Tech Community

Apr 7, 2024 · Artificial Intelligence

Logistic Regression: Definition, Purpose, Structure, Implementation, and Regularization

This article explains logistic regression as a classification algorithm, covering its definition, purpose, mathematical structure, data preparation, core functions such as sigmoid, cost, gradient descent, prediction, model evaluation, decision boundary visualization, feature mapping, and regularization techniques, all illustrated with Python code examples.

Pythonclassificationgradient descent

0 likes · 33 min read

Logistic Regression: Definition, Purpose, Structure, Implementation, and Regularization

DaTaobao Tech

Mar 4, 2024 · Artificial Intelligence

Iris Classification with Machine Learning: Data Exploration and Classic Algorithms

This beginner-friendly guide walks through loading the classic Iris dataset, performing exploratory data analysis, and implementing four fundamental classifiers—Decision Tree, Logistic Regression, Support Vector Machine, and K‑Nearest Neighbors—complete with training, visualization, and accuracy evaluation, illustrating a full machine‑learning workflow.

SVMclassificationdecision tree

0 likes · 22 min read

Iris Classification with Machine Learning: Data Exploration and Classic Algorithms

政采云技术

Oct 10, 2023 · Artificial Intelligence

Predicting Membership Purchase with Logistic Regression: Feature Engineering, Model Training, Evaluation, and Deployment

This article presents a complete workflow for predicting whether users will purchase a membership using logistic regression, covering data collection, feature selection, handling imbalanced samples, model training, hyper‑parameter tuning, threshold optimization, evaluation metrics such as accuracy, precision, recall, AUC, lift, and finally deployment on a big‑data platform with PySpark.

Big Datafeature engineeringlogistic regression

0 likes · 17 min read

Predicting Membership Purchase with Logistic Regression: Feature Engineering, Model Training, Evaluation, and Deployment

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.

Pythonbinary classificationlogistic regression

0 likes · 15 min read

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

Test Development Learning Exchange

Aug 19, 2023 · Artificial Intelligence

Regression Analysis Methods and Code Examples for Various Business Scenarios

This article provides comprehensive regression analysis methods and Python code examples for various business scenarios including e-commerce, market research, healthcare, finance, social media, HR, education, hospitality, marketing, and logistics.

OLS regressionPoisson regressionPython

0 likes · 6 min read

Regression Analysis Methods and Code Examples for Various Business Scenarios

Rare Earth Juejin Tech Community

Aug 6, 2023 · Artificial Intelligence

Explaining Image Recognition: Logistic Regression and Convolutional Neural Networks

This article introduces the principles of image recognition, compares traditional logistic regression with convolutional neural networks, demonstrates their implementation using Python code, visualizes model weights, and explains key concepts such as padding, convolution, pooling, receptive fields, and multi‑layer feature extraction.

Image Recognitionconvolutional neural networkexplainable AI

0 likes · 12 min read

Explaining Image Recognition: Logistic Regression and Convolutional Neural Networks

AntTech

Jul 14, 2023 · Information Security

Open Privacy Computing Protocol SS‑LR: A Secret‑Sharing Based Logistic Regression Framework

The SS‑LR open protocol describes a secret‑sharing based logistic regression algorithm split into four layers—machine learning, secure operators, cryptographic protocol, and network transmission—enabling interoperable, privacy‑preserving data flow and secure multi‑party model training across institutions.

SS-LRdata securitylogistic regression

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Open Privacy Computing Protocol SS‑LR: A Secret‑Sharing Based Logistic Regression Framework

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

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

Model Perspective

Jul 25, 2022 · Artificial Intelligence

How to Interpret Logistic Regression Parameters and Odds Ratios with Python

This article explains the concepts of odds and odds ratios, shows how logistic regression estimates them, and demonstrates practical model fitting and prediction using Python's statsmodels and scikit‑learn libraries with real‑world examples.

Pythonlogistic regressionmachine learning

0 likes · 8 min read

How to Interpret Logistic Regression Parameters and Odds Ratios with Python

Model Perspective

Jul 24, 2022 · Artificial Intelligence

How to Build and Estimate a Logistic Regression Model for Grouped Data

This article explains the construction of logistic regression models, the use of the sigmoid function, maximum likelihood estimation, and least‑squares estimation for grouped data, illustrated with a housing‑purchase case study and complete Python code for fitting and predicting probabilities.

Pythongrouped datalogistic regression

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How to Build and Estimate a Logistic Regression Model for Grouped Data

Python Programming Learning Circle

May 10, 2022 · Artificial Intelligence

Seven Classic Regression Models for Machine Learning

This article introduces regression analysis and explains why it is essential for predictive modeling, then details seven widely used regression techniques—including linear, logistic, polynomial, stepwise, ridge, lasso, and elastic‑net—while offering guidance on selecting the most appropriate model for a given dataset.

lasso regressionlinear regressionlogistic regression

0 likes · 13 min read

Seven Classic Regression Models for Machine Learning

Tencent Cloud Developer

Sep 25, 2020 · Artificial Intelligence

Privacy-Preserving Federated Learning for Financial Risk Control Using Homomorphic Encryption

Tencent Shield‑Federated Computing enables banks to jointly train Gradient Boosted Decision Trees and Logistic Regression with external data owners by using homomorphic encryption to perform encrypted variable and split‑point searches, gradient aggregation, and model updates, delivering near‑centralized accuracy, up to 70 % speed gains, and full data confidentiality for financial risk control.

Federated LearningGradient Boosted Treesfinancial risk control

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Privacy-Preserving Federated Learning for Financial Risk Control Using Homomorphic Encryption

Python Programming Learning Circle

Apr 22, 2020 · Artificial Intelligence

Python Audio‑Based Parkinson’s Disease Detection Using Machine Learning

This tutorial demonstrates how to build a Python library that extracts acoustic measurements from healthy and Parkinson’s disease audio recordings, constructs a machine‑learning dataset, trains a logistic‑regression classifier with scikit‑learn, evaluates its accuracy, and provides functions to load and use the trained model in other applications.

Audio ProcessingParkinson's DiseaseParselmouth

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Python Audio‑Based Parkinson’s Disease Detection Using Machine Learning

Xueersi Online School Tech Team

Mar 13, 2020 · Artificial Intelligence

Predictive Modeling of Student Renewal and Refund Intentions Using Logistic Regression in Online Education

This article describes how logistic regression models are built, iterated, and applied to predict student renewal and refund behavior in an online school, detailing data collection, feature engineering, model training, evaluation, and how the predictions are used to recommend interventions for teachers.

education analyticsfeature engineeringlogistic regression

0 likes · 9 min read

Predictive Modeling of Student Renewal and Refund Intentions Using Logistic Regression in Online Education

Beike Product & Technology

Aug 23, 2019 · Artificial Intelligence

Deep Learning from Theory to Practice: Neural Networks, Logistic Regression, TensorFlow and Keras for Cat Image Classification

This tutorial walks readers through the fundamentals of artificial neural networks, perceptrons, logistic regression, activation and loss functions, gradient descent, and provides end‑to‑end Python implementations using NumPy, TensorFlow, and Keras to build and evaluate a cat‑vs‑non‑cat classifier, complete with code snippets, visual explanations, and performance analysis.

KerasTensorFlowdeep learning

0 likes · 29 min read

Deep Learning from Theory to Practice: Neural Networks, Logistic Regression, TensorFlow and Keras for Cat Image Classification

Didi Tech

May 9, 2019 · Artificial Intelligence

Weber-Fechner Law, Prospect Theory, and Their Data Science Applications

The article explains the Weber‑Fechner law and its role in Prospect Theory, then shows how Didi applies these concepts—using a log‑linear order‑distance model and reference‑point‑based strategy evaluation—to reduce cancellations, improve driver perception, and guide data‑driven product decisions.

DidiProspect TheoryPsychophysics

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Weber-Fechner Law, Prospect Theory, and Their Data Science Applications

JD Tech

Feb 3, 2019 · Artificial Intelligence

Credit Scoring Card Model Based on Logistic Regression: Full Development Process and Implementation

This article explains how to build a credit scoring card model using logistic regression, detailing the full development workflow—from variable selection and WOE encoding to model training, evaluation metrics like AUC and KS, and deployment considerations for risk management.

WOEcredit scoringlogistic regression

0 likes · 8 min read

Credit Scoring Card Model Based on Logistic Regression: Full Development Process and Implementation

JD Tech Talk

Jan 29, 2019 · Artificial Intelligence

Building Credit Scoring Card Models with Logistic Regression: Full Process and Evaluation

This article explains how to construct credit scoring card models using WOE‑encoded variables and logistic regression, describes three card types for different credit scenarios, and details an eleven‑step development workflow including variable selection, modeling, scoring, and performance monitoring.

IVWOEcredit scoring

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Building Credit Scoring Card Models with Logistic Regression: Full Process and Evaluation

Tongcheng Travel Technology Center

Nov 29, 2018 · Artificial Intelligence

Personalized Red Envelope Marketing Using Data Mining and Logistic Regression Models

This article presents a data‑driven personalized red‑envelope marketing solution that cleans and selects features, builds consumption‑demand and red‑envelope‑sensitivity logistic regression models, and iteratively optimizes parameters to lower costs while boosting cross‑project new‑customer conversion rates.

Big DataData MiningRed Envelope

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Personalized Red Envelope Marketing Using Data Mining and Logistic Regression Models