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AntTech

May 22, 2018 · Artificial Intelligence

Unpack Local Model Interpretation for GBDT – Summary and Analysis

This article summarizes the Ant Financial paper presented at DASFAA 2018 that proposes a universal local explanation method for Gradient Boosting Decision Tree models, detailing the problem definition, the PMML‑based algorithm for attributing feature contributions, experimental validation on fraud detection data, and the practical benefits for model transparency and improvement.

GBDTMachine LearningPMML

0 likes · 12 min read

Unpack Local Model Interpretation for GBDT – Summary and Analysis

Qunar Tech Salon

Jan 24, 2017 · Artificial Intelligence

Practical Approaches to Deploying Machine Learning Models: Real‑time SOA, PMML, Rserve, and Spark

This article shares practical engineering experiences for deploying machine learning models in various scenarios—real‑time low‑volume predictions via Rserve or Python‑httpserve, high‑throughput real‑time serving with PMML‑wrapped Java classes, and offline batch predictions using simple shell scripts—detailing tools, performance considerations, and implementation steps.

Machine LearningModel DeploymentPMML

0 likes · 11 min read

Practical Approaches to Deploying Machine Learning Models: Real‑time SOA, PMML, Rserve, and Spark

Ctrip Technology

Jan 5, 2017 · Artificial Intelligence

Practical Approaches to Deploying Machine Learning Models: PMML, Rserve, and Spark in Production

This article shares practical engineering experiences for deploying machine learning models in production, covering three typical scenarios—real‑time small data, real‑time large data, and offline predictions—and detailing how to use PMML, Rserve, Spark, shell scripts, and related tools to meet performance and operational requirements.

Machine LearningModel DeploymentPMML

0 likes · 12 min read

Practical Approaches to Deploying Machine Learning Models: PMML, Rserve, and Spark in Production