decision tree | BestHub

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

Model Perspective

Sep 12, 2023 · Fundamentals

What Is Information Entropy? Definition, Calculation, and Decision Tree Applications

This article explains the concept of information entropy, its mathematical definition, how to compute it for simple events like coin flips and dice rolls, and demonstrates its role in decision‑tree learning by calculating information gain for a watermelon dataset.

decision treeinformation entropyinformation gain

0 likes · 11 min read

What Is Information Entropy? Definition, Calculation, and Decision Tree Applications

Model Perspective

Jan 18, 2023 · Artificial Intelligence

Visualizing Decision Trees for Product Purchase Prediction with scikit-learn and dtreeviz

This tutorial explains how to prepare advertising click data, train a decision‑tree classifier, and generate clear visualizations using scikit‑learn and dtreeviz, while also showing how to inspect individual prediction paths and feature importance.

PythonVisualizationclassification

0 likes · 7 min read

Visualizing Decision Trees for Product Purchase Prediction with scikit-learn and dtreeviz

Model Perspective

Jul 30, 2022 · Artificial Intelligence

How Decision Trees Predict House Locations: From Intuition to Overfitting

This article explains machine learning fundamentals using a house‑location classification example, illustrating how decision trees create split points from features like elevation and price, grow recursively, achieve high training accuracy, and reveal overfitting when evaluated on unseen test data.

Artificial IntelligenceData Visualizationclassification

0 likes · 11 min read

How Decision Trees Predict House Locations: From Intuition to Overfitting

Model Perspective

Jun 19, 2022 · Artificial Intelligence

How Decision Trees Work: From Entropy to Gini Index Explained

This article introduces decision tree algorithms, explains their role in supervised learning for classification and regression, details the construction process, compares information gain and Gini index for attribute selection, and reviews popular tree methods such as ID3, C4.5, and CART with illustrative examples.

C4.5CARTID3

0 likes · 7 min read

How Decision Trees Work: From Entropy to Gini Index Explained

Model Perspective

Jun 13, 2022 · Artificial Intelligence

Understanding Decision Trees: From Basic Process to Watermelon Example

This article explains the fundamentals of decision tree learning, describing its recursive construction, the criteria for splitting nodes using information gain based on entropy, and walks through a classic watermelon dataset example to illustrate how attributes are selected and the final tree is built.

ID3 algorithmclassificationdecision tree

0 likes · 8 min read

Understanding Decision Trees: From Basic Process to Watermelon Example

Tencent Cloud Developer

Nov 19, 2021 · Artificial Intelligence

End‑to‑End Breast Cancer Prediction Solution Using Decision Tree on Tencent Cloud AI Platform

This guide details an end‑to‑end breast‑cancer prediction pipeline on Tencent Cloud, covering offline decision‑tree training with TI‑ONE, model packaging as a PMML service, real‑time feature generation via Oceanus and CKafka, and live inference stored in ClickHouse, all within a secure VPC.

AIFlinkReal-time Streaming

0 likes · 19 min read

End‑to‑End Breast Cancer Prediction Solution Using Decision Tree on Tencent Cloud AI Platform

Python Programming Learning Circle

Aug 10, 2021 · Artificial Intelligence

Building a Decision Tree Model in Python Using Entropy and Gini Impurity

This tutorial walks through creating, visualizing, and exporting two Python decision‑tree classifiers—one using entropy and the other using Gini impurity—by installing required packages, preparing a simple dataset, training the models with scikit‑learn, and rendering the trees with Graphviz.

Gini ImpurityGraphvizPython

0 likes · 11 min read

Building a Decision Tree Model in Python Using Entropy and Gini Impurity

Xianyu Technology

Jul 28, 2020 · Operations

ShenTan: Automated Fault Localization System for Online Services

ShenTan is an automated fault‑localization platform for online services that quickly (under five seconds) pinpoints server‑side issues with developer‑level accuracy by aggregating real‑time metrics, applying a decision‑tree model enriched by expert knowledge and dynamic thresholds, and presenting results through an integrated alert and visualization system, while planning broader endpoint coverage and multi‑tenant support.

Big Dataautomationdecision tree

0 likes · 12 min read

ShenTan: Automated Fault Localization System for Online Services

Tencent Advertising Technology

May 2, 2020 · Artificial Intelligence

How to Use TI-ONE Built‑in Operators for the 2020 Tencent Advertising Algorithm Competition

This tutorial walks you through creating a TI‑ONE project, ingesting competition data, configuring and training a decision‑tree model with built‑in operators, running the workflow, and downloading and uploading the result files for the 2020 Tencent Advertising Algorithm Competition.

TI-ONEalgorithm competitiondata pipeline

0 likes · 7 min read

How to Use TI-ONE Built‑in Operators for the 2020 Tencent Advertising Algorithm Competition

Tencent Cloud Developer

Dec 4, 2018 · Artificial Intelligence

Top 10 Most Popular AI Algorithms

The article reviews the ten most popular AI algorithms—linear and logistic regression, LDA, decision trees, Naive Bayes, K‑Nearest Neighbors, LVQ, SVM, Random Forest, and deep neural networks—explaining their strengths, typical use cases, and why selecting the right model matters given the ‘no free lunch’ principle.

AI algorithmsdecision treedeep neural network

0 likes · 12 min read

Qunar Tech Salon

Oct 15, 2018 · Artificial Intelligence

Introduction to Decision Trees with scikit-learn

This article provides a comprehensive guide to decision tree algorithms, covering their theoretical background, classic use‑cases, scikit‑learn's DecisionTreeClassifier parameters, step‑by‑step Python examples for training, visualizing, and exporting trees, as well as a comparison of ID3, C4.5, and CART methods with their advantages and limitations.

PythonVisualizationclassification

0 likes · 20 min read

Introduction to Decision Trees with scikit-learn

Tencent Cloud Developer

Mar 19, 2018 · Artificial Intelligence

Basic Concepts of Decision Trees

Decision trees are tree-structured classifiers that split data using attributes chosen for maximal purity measured by Gini impurity or entropy, with algorithms like ID3 selecting splits by information gain, while overfitting is mitigated through constraints and pruning techniques such as REP, PEP, and CCP.

Gini ImpurityID3algorithm

0 likes · 13 min read

Efficient Ops

Jan 7, 2018 · Operations

How Tencent Leverages AI to Simplify Massive-Scale Service Monitoring and Root‑Cause Analysis

Tencent's SNG social platform team tackles billion‑scale traffic by integrating AI‑driven anomaly detection, multi‑dimensional monitoring, and decision‑tree based root‑cause analysis, turning complex backend architectures and massive alert volumes into streamlined, actionable insights for faster issue resolution.

AIAnomaly Detectiondecision tree

0 likes · 16 min read

How Tencent Leverages AI to Simplify Massive-Scale Service Monitoring and Root‑Cause Analysis

Architects' Tech Alliance

Nov 14, 2017 · Artificial Intelligence

Explaining Machine Learning to a Child: A Food‑Classification Example

The article uses a simple food‑taste classification scenario to illustrate core machine‑learning concepts such as labeled training data, feature representation, linear scoring models, decision boundaries, over‑fitting, generalisation, and decision‑tree reasoning in a way a child can understand.

AI BasicsEducationclassification

0 likes · 4 min read

Explaining Machine Learning to a Child: A Food‑Classification Example

360 Zhihui Cloud Developer

Oct 31, 2017 · Artificial Intelligence

Master Decision Trees: Concepts, Algorithms, and Python Implementation

This article introduces decision trees in data analysis and machine learning, explains core concepts, compares popular algorithms such as ID3, C4.5, and CART, details their mathematical foundations, and provides a complete Python implementation with code examples for building and visualizing trees.

C4.5ID3Python

0 likes · 10 min read

Master Decision Trees: Concepts, Algorithms, and Python Implementation

Baidu Intelligent Testing

Jul 13, 2016 · Artificial Intelligence

Detecting Offline Merchant Service Issues Using Machine Learning and Big Data at Nuomi

The article describes how Nuomi analyzes refund and complaint data with machine‑learning and big‑data techniques, extracts features for single‑ and multi‑store scenarios, builds decision‑tree models with regional adjustments, and creates an online workflow to promptly intervene on merchants that fail to serve customers.

Big Datacustomer experiencedecision tree

0 likes · 5 min read

Detecting Offline Merchant Service Issues Using Machine Learning and Big Data at Nuomi

Efficient Ops

Jun 14, 2016 · Operations

Automate Fault Root‑Cause Detection in Massive IT Operations

This article explains how large‑scale internet companies can reduce alarm storms and speed up incident resolution by creating an operations ecosystem centered on automated fault root‑cause localization, detailing the challenges, architecture, decision‑tree algorithms, and a four‑step implementation guide.

IT infrastructureautomationdecision tree

0 likes · 11 min read

Automate Fault Root‑Cause Detection in Massive IT Operations

Qunar Tech Salon

Mar 15, 2015 · Artificial Intelligence

Overview of Common Classification Algorithms in Data Mining

This article introduces the concepts of classification and prediction in data mining, outlines their workflow, and provides concise explanations of six widely used classification techniques—decision trees, K‑Nearest Neighbour, Support Vector Machine, Vector Space Model, Bayesian methods, and neural networks—highlighting their principles, advantages, and limitations.

Data MiningSVMbayesian

0 likes · 9 min read

Overview of Common Classification Algorithms in Data Mining