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Huolala Safety Emergency Response Center
Huolala Safety Emergency Response Center
Apr 15, 2026 · Information Security

How to Auto‑Label 10K APIs with 95% Confidence Using Self‑Learning Feature Engineering

This article presents a detailed case study of how a large‑scale API security team built an automated, self‑learning classification system that tags tens of thousands of APIs with business labels, improves model accuracy by five points, and maintains high precision through a confidence‑driven feedback loop.

API SecurityCatBoostSHAP
0 likes · 13 min read
How to Auto‑Label 10K APIs with 95% Confidence Using Self‑Learning Feature Engineering
Huolala Tech
Huolala Tech
Apr 15, 2026 · Information Security

How We Built a Self‑Learning API Classification System for Security

This article details a real‑world case study of how a large logistics platform created an automated, self‑evolving API asset‑classification pipeline—covering data collection, feature engineering, model training with CatBoost, confidence‑based label feedback, and lessons learned—to improve API security monitoring and reduce manual labeling effort.

API SecurityCatBoostSHAP
0 likes · 13 min read
How We Built a Self‑Learning API Classification System for Security
Sohu Tech Products
Sohu Tech Products
Oct 9, 2025 · Artificial Intelligence

Open-Source Kaggle Solution: Predicting Multi-Market Commodity Prices with Tree Models

An open-source, Kaggle‑ranked solution for the Mitsui Commodity Prediction Challenge details data preprocessing, feature engineering, and multiple tree‑based modeling strategies—including multi‑target, single‑target, and price‑difference models—with code, evaluation metrics, and suggestions for further improvements.

CatBoostCommodityFeatureEngineering
0 likes · 17 min read
Open-Source Kaggle Solution: Predicting Multi-Market Commodity Prices with Tree Models
DataFunSummit
DataFunSummit
Mar 22, 2022 · Artificial Intelligence

Housing Price Estimation and Average Price Calculation Using 58.com Data and CatBoost

This article presents a comprehensive overview of 58.com’s real‑estate price system, describes how average prices are computed from platform data, explains three anomaly‑detection methods, and details a CatBoost‑based machine‑learning model for automated house valuation, including feature engineering and evaluation metrics.

CatBoostReal Estate Dataanomaly detection
0 likes · 15 min read
Housing Price Estimation and Average Price Calculation Using 58.com Data and CatBoost
Python Programming Learning Circle
Python Programming Learning Circle
Dec 21, 2021 · Artificial Intelligence

Introduction to CatBoost: Features, Advantages, and Practical Implementation

This article introduces CatBoost, outlines its key advantages such as automatic handling of categorical features, symmetric trees, and feature combination, and provides a step‑by‑step Python tutorial—including data preparation, model training, visualization, and feature importance analysis—using a CTR prediction dataset.

CatBoostModel EvaluationPython
0 likes · 5 min read
Introduction to CatBoost: Features, Advantages, and Practical Implementation
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