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Data Party THU
Data Party THU
Sep 14, 2025 · Artificial Intelligence

How Machine Learning Predicts Genetic Variant Penetrance Across Populations

Researchers at Mount Sinai Icahn School of Medicine used gradient‑boosting trees on over one million electronic health records to build machine‑learning models for ten hereditary diseases, quantifying the penetrance of genetic variants and demonstrating how probabilistic risk scores can improve clinical interpretation and patient management.

Risk Predictionclinical geneticselectronic health records
0 likes · 8 min read
How Machine Learning Predicts Genetic Variant Penetrance Across Populations
Data Party THU
Data Party THU
Aug 18, 2025 · Artificial Intelligence

Unlock XGBoost Performance: Master the Core Parameters

This article provides a detailed, visual guide to XGBoost's most important hyper‑parameters—such as max_depth, min_child_weight, learning_rate, gamma, subsample, colsample_bytree, scale_pos_weight, alpha, and lambda—explaining how each influences tree complexity, regularization, and model generalization, and offering practical examples for effective tuning.

Model OptimizationRegularizationXGBoost
0 likes · 12 min read
Unlock XGBoost Performance: Master the Core Parameters
Sohu Tech Products
Sohu Tech Products
Mar 6, 2024 · Artificial Intelligence

Mastering Regression: A Comprehensive Guide to Linear and Non‑Linear Models

This article provides an in‑depth overview of regression prediction, covering linear models like OLS, Lasso, Ridge, and Bayesian approaches, as well as non‑linear techniques such as tree ensembles, SVR, KNN, neural networks, and advanced deep learning frameworks for tabular data.

Deep Learninggradient boostinglinear models
0 likes · 13 min read
Mastering Regression: A Comprehensive Guide to Linear and Non‑Linear Models
IT Services Circle
IT Services Circle
Mar 6, 2024 · Artificial Intelligence

Comprehensive Overview of Ten Regression Algorithms with Core Concepts and Code Examples

This article provides a comprehensive summary of ten regression algorithms—including linear, ridge, Lasso, decision tree, random forest, gradient boosting, SVR, XGBoost, LightGBM, and neural network regression—detailing their principles, advantages, disadvantages, suitable scenarios, and offering core Python code examples for each.

Pythongradient boostingmachine learning
0 likes · 33 min read
Comprehensive Overview of Ten Regression Algorithms with Core Concepts and Code Examples
AntTech
AntTech
Aug 16, 2023 · Information Security

Ant Group Research Institute Presents Two First-Author Papers at USENIX Security 2023 on Secure MPC for GBDT Training and Efficient 3PC for Binary Circuits

At the 32nd USENIX Security Symposium in Anaheim, Ant Group’s Research Institute sponsored the event and showcased two first‑author papers—one introducing the Squirrel framework for fast, secure two‑party computation of Gradient Boosting Decision Trees, and another proposing an efficient 3‑party protocol for binary circuits in maliciously‑secure DNN inference.

DNN inferenceMPCUSENIX Security
0 likes · 3 min read
Ant Group Research Institute Presents Two First-Author Papers at USENIX Security 2023 on Secure MPC for GBDT Training and Efficient 3PC for Binary Circuits
Model Perspective
Model Perspective
Oct 1, 2022 · Artificial Intelligence

Boost Your Models with LightGBM: Fast, Accurate Gradient Boosting in Python

This article introduces LightGBM, a high‑performance gradient boosting framework, explains its advantages over XGBoost, and provides step‑by‑step Python code for building classification and regression models on the Iris dataset, including model training, evaluation, and visualizing feature importance and tree structures.

LightGBMPythonclassification
0 likes · 5 min read
Boost Your Models with LightGBM: Fast, Accurate Gradient Boosting in Python
Code DAO
Code DAO
Dec 18, 2021 · Artificial Intelligence

Accelerating Gradient Boosting with CatBoost

This article explains how CatBoost implements gradient boosting, handles categorical features without preprocessing, lists its key advantages, details common training parameters, and provides a step‑by‑step regression example with code for fitting, cross‑validation, grid search, tree visualization, and parameter inspection.

CatBoostgradient boostinghyperparameter tuning
0 likes · 7 min read
Accelerating Gradient Boosting with CatBoost
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 14, 2018 · Artificial Intelligence

How Alibaba’s UC Team Boosted Short‑Video Recommendations with FM+GBM

This article details the evolution of Alibaba's short‑video feed ranking system, from a Wide&Deep CTR model to a hybrid Factorization‑Machine and Gradient‑Boosted‑Tree approach, describing feature engineering, model architecture, experimental results, lessons learned, and future directions toward duration‑based relevance.

factorization machinesgradient boostingmachine learning
0 likes · 11 min read
How Alibaba’s UC Team Boosted Short‑Video Recommendations with FM+GBM
Tencent Advertising Technology
Tencent Advertising Technology
May 28, 2018 · Artificial Intelligence

Winning Approach of the Tencent Advertising Algorithm Competition: Feature Engineering, Model Selection, and Future Work

The team from Jilin University, Harbin Institute of Technology, and Beijing University of Posts and Telecommunications shares their winning strategy for the Tencent Advertising Algorithm Competition, detailing their feature engineering, model selection, and future work to handle large‑scale data challenges.

AdvertisingDeep LearningModel Selection
0 likes · 4 min read
Winning Approach of the Tencent Advertising Algorithm Competition: Feature Engineering, Model Selection, and Future Work
Qunar Tech Salon
Qunar Tech Salon
Apr 3, 2018 · Artificial Intelligence

An Introduction to Gradient Boosting Decision Trees (GBDT) and Its Applications in Consumer Finance

Gradient Boosting Decision Tree (GBDT) is an ensemble learning method that combines additive and gradient boosting, detailed with its mathematical foundations, regression and classification algorithms, implementation using scikit‑learn, and a real‑world consumer‑finance fraud detection case achieving high AUC and KS metrics.

GBDTPythonconsumer finance
0 likes · 11 min read
An Introduction to Gradient Boosting Decision Trees (GBDT) and Its Applications in Consumer Finance