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Test Development Learning Exchange
Test Development Learning Exchange
Nov 22, 2024 · Artificial Intelligence

Introduction to Data Modeling with Scikit-Learn

This article provides a comprehensive guide to using Scikit-Learn for data modeling, covering linear regression and decision tree algorithms, including data preparation, model training, evaluation metrics, and visualization techniques for predictive analysis.

Data ModelingPythondata science
0 likes · 4 min read
Introduction to Data Modeling with Scikit-Learn
AntTech
AntTech
Nov 21, 2022 · Artificial Intelligence

An Adaptive Framework for Confidence-Constraint Rule Set Learning in Large Datasets

The paper introduces a constraint‑adaptive rule‑set learning framework (CRSL) that combines a constraint‑aware decision‑tree miner (CARM), a rule‑sorting filter, and a Bayesian rule‑combination selector (CBRS), achieving superior performance and interpretability on benchmark and massive industrial fraud‑detection data and being deployed in Alipay’s risk‑analysis platform.

Bayesian methodsconstraint optimizationdecision trees
0 likes · 10 min read
An Adaptive Framework for Confidence-Constraint Rule Set Learning in Large Datasets
Xianyu Technology
Xianyu Technology
Jun 4, 2020 · Artificial Intelligence

NBDT: Neural-Backed Decision Trees for Interpretable Image Classification

NBDT (Neural‑Backed Decision Trees) merges a pretrained CNN with a WordNet‑derived hierarchical tree, using the network’s final‑layer weights as class embeddings and a combined classification loss, to deliver state‑of‑the‑art image classification that remains interpretable through explicit hierarchical reasoning.

CNNExplainable Machine LearningNBDT
0 likes · 11 min read
NBDT: Neural-Backed Decision Trees for Interpretable Image Classification
Tencent Cloud Developer
Tencent Cloud Developer
Oct 18, 2018 · Artificial Intelligence

10 Machine Learning Algorithms You Should Know to Become a Data Scientist

This article outlines the essential role of a data scientist and introduces ten fundamental machine‑learning algorithms—including PCA/SVD, OLS and polynomial regression, regularized linear models, K‑Means, logistic regression, SVM, feed‑forward, convolutional and recurrent neural networks, CRFs, ensemble trees, and reinforcement‑learning methods—while linking to popular Python libraries and tutorials.

AlgorithmsPCASVM
0 likes · 10 min read
10 Machine Learning Algorithms You Should Know to Become a Data Scientist